From 7d310641eed72a89fd88e8ac197a10a471bd86fd Mon Sep 17 00:00:00 2001
From: olivroy <olivierroy71@hotmail.com>
Date: Fri, 15 Mar 2024 11:22:10 -0400
Subject: [PATCH 1/9] remove docs directory (gh pages)

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-naniar.njtierney.com
diff --git a/docs/CONDUCT.html b/docs/CONDUCT.html
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-<h3 id="please-contribute">Please contribute!<a class="anchor" aria-label="anchor" href="#please-contribute"></a></h3>
-<p>We love collaboration.</p>
-</div>
-<div class="section level3">
-<h3 id="bugs">Bugs?<a class="anchor" aria-label="anchor" href="#bugs"></a></h3>
-<ul><li>Submit an issue on the <a href="https://github.com/%7Bowner%7D/%7Brepo%7D/issues" class="external-link">Issues page</a>
-</li>
-</ul></div>
-<div class="section level3">
-<h3 id="code-contributions">Code contributions<a class="anchor" aria-label="anchor" href="#code-contributions"></a></h3>
-<ul><li>Fork this repo to your Github account</li>
-<li>Clone your version on your account down to your machine from your account, e.g,. <code>git clone https://github.com/&lt;yourgithubusername&gt;/{repo}.git</code>
-</li>
-<li>Make sure to track progress upstream (i.e., on our version of <code>{repo}</code> at <code>{owner}/{repo}</code>) by doing <code>git remote add upstream https://github.com/{owner}/{repo}.git</code>. Before making changes make sure to pull changes in from upstream by doing either <code>git fetch upstream</code> then merge later or <code>git pull upstream</code> to fetch and merge in one step</li>
-<li>Make your changes (bonus points for making changes on a new feature branch)</li>
-<li>Push up to your account</li>
-<li>Submit a pull request to home base (likely master branch, but check to make sure) at <code>{owner}/{repo}</code>
-</li>
-</ul></div>
-<div class="section level3">
-<h3 id="prefer-to-email">Prefer to Email?<a class="anchor" aria-label="anchor" href="#prefer-to-email"></a></h3>
-<p>I will be able to better help you if you post an issue but otherwise, you can find my contact details in the <code>DESCRIPTION</code> file of this repo.</p>
-</div>
-<div class="section level3">
-<h3 id="thanks-for-contributing">Thanks for contributing!<a class="anchor" aria-label="anchor" href="#thanks-for-contributing"></a></h3>
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-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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diff --git a/docs/LICENSE-text.html b/docs/LICENSE-text.html
deleted file mode 100644
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--- a/docs/LICENSE-text.html
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-<!DOCTYPE html>
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-  <a class="nav-link" href="articles/naniar-visualisation.html">Gallery</a>
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-    <a class="dropdown-item" href="articles/replace-with-na.html">Replace with NA</a>
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-      
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-<pre>YEAR: 2016-2018
-COPYRIGHT HOLDER: Nicholas Tierney
-</pre>
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-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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diff --git a/docs/LICENSE.html b/docs/LICENSE.html
deleted file mode 100644
index 797cdb57..00000000
--- a/docs/LICENSE.html
+++ /dev/null
@@ -1,114 +0,0 @@
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-  <a href="articles/naniar-visualisation.html">Gallery</a>
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-  <a href="articles/replace-with-na.html">Replace with NA</a>
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-</div><!--/.navbar -->
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-      </header>
-
-      <div class="row">
-  <div class="contents col-md-12">
-    <div class="page-header">
-      <h1>License</h1>
-    </div>
-
-<pre>YEAR: 2016
-COPYRIGHT HOLDER: Nicholas Tierney
-</pre>
-
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-      <img src="../logo.png" class="logo" alt=""><h1>Exploring Imputed Values</h1>
-                        <h4 data-toc-skip class="author">Nicholas
-Tierney</h4>
-            
-            <h4 data-toc-skip class="date">2023-05-01</h4>
-      
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/vignettes/exploring-imputed-values.Rmd" class="external-link"><code>vignettes/exploring-imputed-values.Rmd</code></a></small>
-      <div class="d-none name"><code>exploring-imputed-values.Rmd</code></div>
-    </div>
-
-    
-    
-<p>Imputating missing values is an iterative process.
-<code>naniar</code> aims to make it easier to manage imputed values by
-providing the <code>nabular</code> data structure to simplify managing
-missingness. This vignette provides some useful recipes for imputing and
-exploring imputed data.</p>
-<p><code>naniar</code> implements a few imputation methods to facilitate
-exploration and visualisations, which were not otherwise available:
-<code>impute_below</code>, and <code>impute_mean</code>. For single
-imputation, the R package <code>simputation</code> works very well with
-<code>naniar</code>, and provides the main example given.</p>
-<div class="section level2">
-<h2 id="imputing-and-tracking-missing-values">Imputing and tracking missing values<a class="anchor" aria-label="anchor" href="#imputing-and-tracking-missing-values"></a>
-</h2>
-</div>
-<div class="section level2">
-<h2 id="using-impute_below">Using <code>impute_below</code><a class="anchor" aria-label="anchor" href="#using-impute_below"></a>
-</h2>
-<p><code>impute_below</code> imputes values below the minimum of the
-data, with some noise to reduce overplotting. The amount data is imputed
-below, and the amount of jitter, can be changed by changing the
-arguments <code>prop_below</code> and <code>jitter</code>.</p>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span>
-<span><span class="co">#&gt; </span></span>
-<span><span class="co">#&gt; Attaching package: 'dplyr'</span></span>
-<span><span class="co">#&gt; The following objects are masked from 'package:stats':</span></span>
-<span><span class="co">#&gt; </span></span>
-<span><span class="co">#&gt;     filter, lag</span></span>
-<span><span class="co">#&gt; The following objects are masked from 'package:base':</span></span>
-<span><span class="co">#&gt; </span></span>
-<span><span class="co">#&gt;     intersect, setdiff, setequal, union</span></span>
-<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/njtierney/naniar" class="external-link">naniar</a></span><span class="op">)</span></span>
-<span></span>
-<span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/impute_below_at.html">impute_below_at</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html" class="external-link">vars</a></span><span class="op">(</span><span class="va">Ozone</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">Ozone</span>, <span class="va">Solar.R</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="co">#&gt;       Ozone Solar.R</span></span>
-<span><span class="co">#&gt; 1  41.00000     190</span></span>
-<span><span class="co">#&gt; 2  36.00000     118</span></span>
-<span><span class="co">#&gt; 3  12.00000     149</span></span>
-<span><span class="co">#&gt; 4  18.00000     313</span></span>
-<span><span class="co">#&gt; 5 -19.72321      NA</span></span>
-<span><span class="co">#&gt; 6  28.00000      NA</span></span></code></pre></div>
-</div>
-<div class="section level2">
-<h2 id="using-impute_mean">Using <code>impute_mean</code><a class="anchor" aria-label="anchor" href="#using-impute_mean"></a>
-</h2>
-<p>The mean can be imputed using <code>impute_mean</code>, and is useful
-to explore structure in missingness, but are not recommended for use in
-analysis. Similar to <code>simputation</code>, each <code>impute_</code>
-function returns the data with values imputed.</p>
-<p>Imputation functions in <code>naniar</code> implement “scoped
-variants” for imputation: <code>_all</code>, <code>_at</code> and
-<code>_if</code>.</p>
-<p>This means:</p>
-<ul>
-<li>
-<code>_all</code> operates on all columns</li>
-<li>
-<code>_at</code> operates on specific columns, and</li>
-<li>
-<code>_if</code> operates on columns that meet some condition (such
-as <code>is.numeric</code> or <code>is.character</code>).</li>
-</ul>
-<p>If the <code>impute_</code> functions are used as-is - e.g.,
-<code>impute_mean</code>, this will work on a single vector, but not a
-data.frame.</p>
-<p>Some examples for <code>impute_mean</code> are now given:</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="fu"><a href="../reference/impute_mean.html">impute_mean</a></span><span class="op">(</span><span class="va">oceanbuoys</span><span class="op">$</span><span class="va">air_temp_c</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="co">#&gt; [1] 27.15 27.02 27.00 26.93 26.84 26.94</span></span>
-<span></span>
-<span><span class="fu"><a href="../reference/scoped-impute_mean.html">impute_mean_at</a></span><span class="op">(</span><span class="va">oceanbuoys</span>, .vars <span class="op">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html" class="external-link">vars</a></span><span class="op">(</span><span class="va">air_temp_c</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 6 × 8</span></span></span>
-<span><span class="co">#&gt;    year latitude longitude sea_temp_c air_temp_c humidity wind_ew wind_ns</span></span>
-<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       27.6       27.1     79.6   -<span style="color: #BB0000;">6.40</span>    5.40</span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       27.5       27.0     75.8   -<span style="color: #BB0000;">5.30</span>    5.30</span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       27.6       27       76.5   -<span style="color: #BB0000;">5.10</span>    4.5 </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       27.6       26.9     76.2   -<span style="color: #BB0000;">4.90</span>    2.5 </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">5</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       27.6       26.8     76.4   -<span style="color: #BB0000;">3.5</span>     4.10</span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">6</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       27.8       26.9     76.7   -<span style="color: #BB0000;">4.40</span>    1.60</span></span>
-<span></span>
-<span><span class="fu"><a href="../reference/scoped-impute_mean.html">impute_mean_if</a></span><span class="op">(</span><span class="va">oceanbuoys</span>, .predicate <span class="op">=</span> <span class="va">is.integer</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 6 × 8</span></span></span>
-<span><span class="co">#&gt;    year latitude longitude sea_temp_c air_temp_c humidity wind_ew wind_ns</span></span>
-<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       27.6       27.1     79.6   -<span style="color: #BB0000;">6.40</span>    5.40</span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       27.5       27.0     75.8   -<span style="color: #BB0000;">5.30</span>    5.30</span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       27.6       27       76.5   -<span style="color: #BB0000;">5.10</span>    4.5 </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       27.6       26.9     76.2   -<span style="color: #BB0000;">4.90</span>    2.5 </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">5</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       27.6       26.8     76.4   -<span style="color: #BB0000;">3.5</span>     4.10</span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">6</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       27.8       26.9     76.7   -<span style="color: #BB0000;">4.40</span>    1.60</span></span>
-<span></span>
-<span><span class="fu"><a href="../reference/scoped-impute_mean.html">impute_mean_all</a></span><span class="op">(</span><span class="va">oceanbuoys</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 6 × 8</span></span></span>
-<span><span class="co">#&gt;    year latitude longitude sea_temp_c air_temp_c humidity wind_ew wind_ns</span></span>
-<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       27.6       27.1     79.6   -<span style="color: #BB0000;">6.40</span>    5.40</span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       27.5       27.0     75.8   -<span style="color: #BB0000;">5.30</span>    5.30</span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       27.6       27       76.5   -<span style="color: #BB0000;">5.10</span>    4.5 </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       27.6       26.9     76.2   -<span style="color: #BB0000;">4.90</span>    2.5 </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">5</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       27.6       26.8     76.4   -<span style="color: #BB0000;">3.5</span>     4.10</span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">6</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       27.8       26.9     76.7   -<span style="color: #BB0000;">4.40</span>    1.60</span></span></code></pre></div>
-<p>When we impute data like this, we cannot identify where the imputed
-values are - we need to track them. We can track the imputed values
-using the <code>nabular</code> format of the data.</p>
-<div class="section level4">
-<h4 id="track-imputed-values-using-nabular-data">Track imputed values using nabular data<a class="anchor" aria-label="anchor" href="#track-imputed-values-using-nabular-data"></a>
-</h4>
-<p>We can track the missing values by combining the verbs
-<code>bind_shadow</code>, <code>impute_</code>,
-<code>add_label_shadow</code>. We can then refer to missing values by
-their shadow variable, <code>_NA</code>. The
-<code>add_label_shadow</code> function adds an additional column called
-<code>any_missing</code>, which tells us if any observation has a
-missing value.</p>
-<div class="section level5">
-<h5 id="imputing-values-using-simputation">Imputing values using simputation<a class="anchor" aria-label="anchor" href="#imputing-values-using-simputation"></a>
-</h5>
-<p>We can impute the data using the easy-to-use <code>simputation</code>
-package, and then track the missingness using <code>bind_shadow</code>
-and <code>add_label_shadow</code>:</p>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/markvanderloo/simputation" class="external-link">simputation</a></span><span class="op">)</span></span>
-<span><span class="co">#&gt; </span></span>
-<span><span class="co">#&gt; Attaching package: 'simputation'</span></span>
-<span><span class="co">#&gt; The following object is masked from 'package:naniar':</span></span>
-<span><span class="co">#&gt; </span></span>
-<span><span class="co">#&gt;     impute_median</span></span>
-<span><span class="va">ocean_imp</span> <span class="op">&lt;-</span> <span class="va">oceanbuoys</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/bind_shadow.html">bind_shadow</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/pkg/simputation/man/impute_lm.html" class="external-link">impute_lm</a></span><span class="op">(</span><span class="va">air_temp_c</span> <span class="op">~</span> <span class="va">wind_ew</span> <span class="op">+</span> <span class="va">wind_ns</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/pkg/simputation/man/impute_lm.html" class="external-link">impute_lm</a></span><span class="op">(</span><span class="va">humidity</span> <span class="op">~</span>  <span class="va">wind_ew</span> <span class="op">+</span> <span class="va">wind_ns</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/pkg/simputation/man/impute_lm.html" class="external-link">impute_lm</a></span><span class="op">(</span><span class="va">sea_temp_c</span> <span class="op">~</span>  <span class="va">wind_ew</span> <span class="op">+</span> <span class="va">wind_ns</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/add_label_shadow.html">add_label_shadow</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-<p>We can then show the previously missing (now imputed!) data in a
-scatterplot with ggplot2 by setting the <code>color</code> aesthetic in
-ggplot to <code>any_missing</code>:</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span>
-<span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">ocean_imp</span>,</span>
-<span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">air_temp_c</span>,</span>
-<span>           y <span class="op">=</span> <span class="va">humidity</span>,</span>
-<span>           color <span class="op">=</span> <span class="va">any_missing</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_point.html" class="external-link">geom_point</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_brewer.html" class="external-link">scale_color_brewer</a></span><span class="op">(</span>palette <span class="op">=</span> <span class="st">"Dark2"</span><span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/theme.html" class="external-link">theme</a></span><span class="op">(</span>legend.position <span class="op">=</span> <span class="st">"bottom"</span><span class="op">)</span></span></code></pre></div>
-<p><img src="exploring-imputed-values_files/figure-html/ocean-imp-air-temp-humidity-1.png" width="700"></p>
-<p>Or, if you want to look at one variable, you can look at a density
-plot of one variable, using <code>fill = any_missing</code></p>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">ocean_imp</span>,</span>
-<span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">air_temp_c</span>,</span>
-<span>           fill <span class="op">=</span> <span class="va">any_missing</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_density.html" class="external-link">geom_density</a></span><span class="op">(</span>alpha <span class="op">=</span> <span class="fl">0.3</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_brewer.html" class="external-link">scale_fill_brewer</a></span><span class="op">(</span>palette <span class="op">=</span> <span class="st">"Dark2"</span><span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/theme.html" class="external-link">theme</a></span><span class="op">(</span>legend.position <span class="op">=</span> <span class="st">"bottom"</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">ocean_imp</span>,</span>
-<span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">humidity</span>,</span>
-<span>           fill <span class="op">=</span> <span class="va">any_missing</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_density.html" class="external-link">geom_density</a></span><span class="op">(</span>alpha <span class="op">=</span> <span class="fl">0.3</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_brewer.html" class="external-link">scale_fill_brewer</a></span><span class="op">(</span>palette <span class="op">=</span> <span class="st">"Dark2"</span><span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/theme.html" class="external-link">theme</a></span><span class="op">(</span>legend.position <span class="op">=</span> <span class="st">"bottom"</span><span class="op">)</span></span></code></pre></div>
-<p><img src="exploring-imputed-values_files/figure-html/ocean-imp-density-1.png" width="49%"><img src="exploring-imputed-values_files/figure-html/ocean-imp-density-2.png" width="49%"></p>
-<p>We can also compare imputed values to complete cases by grouping by
-<code>any_missing</code>, and summarising.</p>
-<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">ocean_imp</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">any_missing</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise_all.html" class="external-link">summarise_at</a></span><span class="op">(</span>.vars <span class="op">=</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/vars.html" class="external-link">vars</a></span><span class="op">(</span><span class="va">air_temp_c</span><span class="op">)</span>,</span>
-<span>               .funs <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span></span>
-<span>                 min <span class="op">=</span> <span class="op">~</span> <span class="fu"><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">min</a></span><span class="op">(</span><span class="va">.x</span>, na.rm <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>, </span>
-<span>                 mean <span class="op">=</span> <span class="op">~</span> <span class="fu"><a href="https://rdrr.io/r/base/mean.html" class="external-link">mean</a></span><span class="op">(</span><span class="va">.x</span>, na.rm <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>, </span>
-<span>                 median <span class="op">=</span> <span class="op">~</span> <span class="fu"><a href="https://rdrr.io/r/stats/median.html" class="external-link">median</a></span><span class="op">(</span><span class="va">.x</span>, na.rm <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>, </span>
-<span>                 max <span class="op">=</span> <span class="op">~</span> <span class="fu"><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">max</a></span><span class="op">(</span><span class="va">.x</span>, na.rm <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span>
-<span>              <span class="op">)</span><span class="op">)</span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 2 × 5</span></span></span>
-<span><span class="co">#&gt;   any_missing   min  mean median   max</span></span>
-<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>       <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> Missing      21.4  23.9   24.4  25.2</span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> Not Missing  22.1  25.3   25.8  28.5</span></span></code></pre></div>
-</div>
-</div>
-</div>
-<div class="section level2">
-<h2 id="improving-imputations">Improving imputations<a class="anchor" aria-label="anchor" href="#improving-imputations"></a>
-</h2>
-<p>One thing that we notice with our imputations are that they aren’t
-very good - we can improve upon the imputation by including the
-variables year and latitude and longitude:</p>
-<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">ocean_imp_yr</span> <span class="op">&lt;-</span> <span class="va">oceanbuoys</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/bind_shadow.html">bind_shadow</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/pkg/simputation/man/impute_lm.html" class="external-link">impute_lm</a></span><span class="op">(</span><span class="va">air_temp_c</span> <span class="op">~</span> <span class="va">wind_ew</span> <span class="op">+</span> <span class="va">wind_ns</span> <span class="op">+</span> <span class="va">year</span> <span class="op">+</span> <span class="va">longitude</span> <span class="op">+</span> <span class="va">latitude</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/pkg/simputation/man/impute_lm.html" class="external-link">impute_lm</a></span><span class="op">(</span><span class="va">humidity</span> <span class="op">~</span>  <span class="va">wind_ew</span> <span class="op">+</span> <span class="va">wind_ns</span> <span class="op">+</span> <span class="va">year</span> <span class="op">+</span> <span class="va">longitude</span> <span class="op">+</span> <span class="va">latitude</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/pkg/simputation/man/impute_lm.html" class="external-link">impute_lm</a></span><span class="op">(</span><span class="va">sea_temp_c</span> <span class="op">~</span>  <span class="va">wind_ew</span> <span class="op">+</span> <span class="va">wind_ns</span> <span class="op">+</span> <span class="va">year</span> <span class="op">+</span> <span class="va">longitude</span> <span class="op">+</span> <span class="va">latitude</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/add_label_shadow.html">add_label_shadow</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">ocean_imp_yr</span>,</span>
-<span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">air_temp_c</span>,</span>
-<span>           y <span class="op">=</span> <span class="va">humidity</span>,</span>
-<span>           color <span class="op">=</span> <span class="va">any_missing</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_point.html" class="external-link">geom_point</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_brewer.html" class="external-link">scale_color_brewer</a></span><span class="op">(</span>palette <span class="op">=</span> <span class="st">"Dark2"</span><span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/theme.html" class="external-link">theme</a></span><span class="op">(</span>legend.position <span class="op">=</span> <span class="st">"bottom"</span><span class="op">)</span></span></code></pre></div>
-<p><img src="exploring-imputed-values_files/figure-html/ggplot-air-temp-humidity-1.png" width="700"></p>
-</div>
-<div class="section level2">
-<h2 id="other-imputation-approaches">Other imputation approaches<a class="anchor" aria-label="anchor" href="#other-imputation-approaches"></a>
-</h2>
-<p>Not all imputation packages return data in tidy</p>
-<div class="section level3">
-<h3 id="hmisc-aregimpute">Hmisc aregImpute<a class="anchor" aria-label="anchor" href="#hmisc-aregimpute"></a>
-</h3>
-<p>We can explore using a single imputation of
-<code><a href="https://rdrr.io/pkg/Hmisc/man/aregImpute.html" class="external-link">Hmisc::aregImpute()</a></code>, which allows for multiple imputation
-with bootstrapping, additive regression, and predictive mean matching.
-We are going to explore predicting mean matching, and single
-imputation.</p>
-<div class="sourceCode" id="cb9"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb9-1"><a href="#cb9-1" aria-hidden="true" tabindex="-1"></a></span>
-<span id="cb9-2"><a href="#cb9-2" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(Hmisc)</span>
-<span id="cb9-3"><a href="#cb9-3" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; </span></span>
-<span id="cb9-4"><a href="#cb9-4" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; Attaching package: 'Hmisc'</span></span>
-<span id="cb9-5"><a href="#cb9-5" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; The following object is masked from 'package:simputation':</span></span>
-<span id="cb9-6"><a href="#cb9-6" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; </span></span>
-<span id="cb9-7"><a href="#cb9-7" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt;     impute</span></span>
-<span id="cb9-8"><a href="#cb9-8" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; The following objects are masked from 'package:dplyr':</span></span>
-<span id="cb9-9"><a href="#cb9-9" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; </span></span>
-<span id="cb9-10"><a href="#cb9-10" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt;     src, summarize</span></span>
-<span id="cb9-11"><a href="#cb9-11" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; The following objects are masked from 'package:base':</span></span>
-<span id="cb9-12"><a href="#cb9-12" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; </span></span>
-<span id="cb9-13"><a href="#cb9-13" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt;     format.pval, units</span></span>
-<span id="cb9-14"><a href="#cb9-14" aria-hidden="true" tabindex="-1"></a></span>
-<span id="cb9-15"><a href="#cb9-15" aria-hidden="true" tabindex="-1"></a>aq_imp <span class="ot">&lt;-</span> <span class="fu">aregImpute</span>(<span class="sc">~</span>Ozone <span class="sc">+</span> Temp <span class="sc">+</span> Wind <span class="sc">+</span> Solar.R,</span>
-<span id="cb9-16"><a href="#cb9-16" aria-hidden="true" tabindex="-1"></a>                     <span class="at">n.impute =</span> <span class="dv">1</span>,</span>
-<span id="cb9-17"><a href="#cb9-17" aria-hidden="true" tabindex="-1"></a>                     <span class="at">type =</span> <span class="st">"pmm"</span>,</span>
-<span id="cb9-18"><a href="#cb9-18" aria-hidden="true" tabindex="-1"></a>                     <span class="at">data =</span> airquality)</span>
-<span id="cb9-19"><a href="#cb9-19" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; Iteration 1 </span></span>
-<span id="cb9-20"><a href="#cb9-20" aria-hidden="true" tabindex="-1"></a>Iteration <span class="dv">2</span> </span>
-<span id="cb9-21"><a href="#cb9-21" aria-hidden="true" tabindex="-1"></a>Iteration <span class="dv">3</span> </span>
-<span id="cb9-22"><a href="#cb9-22" aria-hidden="true" tabindex="-1"></a>Iteration <span class="dv">4</span> </span>
-<span id="cb9-23"><a href="#cb9-23" aria-hidden="true" tabindex="-1"></a></span>
-<span id="cb9-24"><a href="#cb9-24" aria-hidden="true" tabindex="-1"></a>aq_imp</span>
-<span id="cb9-25"><a href="#cb9-25" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; </span></span>
-<span id="cb9-26"><a href="#cb9-26" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; Multiple Imputation using Bootstrap and PMM</span></span>
-<span id="cb9-27"><a href="#cb9-27" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; </span></span>
-<span id="cb9-28"><a href="#cb9-28" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; aregImpute(formula = ~Ozone + Temp + Wind + Solar.R, data = airquality, </span></span>
-<span id="cb9-29"><a href="#cb9-29" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt;     n.impute = 1, type = "pmm")</span></span>
-<span id="cb9-30"><a href="#cb9-30" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; </span></span>
-<span id="cb9-31"><a href="#cb9-31" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; n: 153   p: 4    Imputations: 1      nk: 3 </span></span>
-<span id="cb9-32"><a href="#cb9-32" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; </span></span>
-<span id="cb9-33"><a href="#cb9-33" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; Number of NAs:</span></span>
-<span id="cb9-34"><a href="#cb9-34" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt;   Ozone    Temp    Wind Solar.R </span></span>
-<span id="cb9-35"><a href="#cb9-35" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt;      37       0       0       7 </span></span>
-<span id="cb9-36"><a href="#cb9-36" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; </span></span>
-<span id="cb9-37"><a href="#cb9-37" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt;         type d.f.</span></span>
-<span id="cb9-38"><a href="#cb9-38" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; Ozone      s    2</span></span>
-<span id="cb9-39"><a href="#cb9-39" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; Temp       s    2</span></span>
-<span id="cb9-40"><a href="#cb9-40" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; Wind       s    2</span></span>
-<span id="cb9-41"><a href="#cb9-41" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; Solar.R    s    1</span></span>
-<span id="cb9-42"><a href="#cb9-42" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; </span></span>
-<span id="cb9-43"><a href="#cb9-43" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; Transformation of Target Variables Forced to be Linear</span></span>
-<span id="cb9-44"><a href="#cb9-44" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; </span></span>
-<span id="cb9-45"><a href="#cb9-45" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; R-squares for Predicting Non-Missing Values for Each Variable</span></span>
-<span id="cb9-46"><a href="#cb9-46" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; Using Last Imputations of Predictors</span></span>
-<span id="cb9-47"><a href="#cb9-47" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt;   Ozone Solar.R </span></span>
-<span id="cb9-48"><a href="#cb9-48" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt;   0.667   0.224</span></span></code></pre></div>
-<p>We are now going to get our data into <code>nabular</code> form, and
-then insert the imputed values:</p>
-<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="co"># nabular form!</span></span>
-<span><span class="va">aq_nab</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/nabular.html">nabular</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span>  <span class="fu"><a href="../reference/add_label_shadow.html">add_label_shadow</a></span><span class="op">(</span><span class="op">)</span></span>
-<span></span>
-<span><span class="co"># insert imputed values</span></span>
-<span><span class="va">aq_nab</span><span class="op">$</span><span class="va">Ozone</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html" class="external-link">is.na</a></span><span class="op">(</span><span class="va">aq_nab</span><span class="op">$</span><span class="va">Ozone</span><span class="op">)</span><span class="op">]</span> <span class="op">&lt;-</span> <span class="va">aq_imp</span><span class="op">$</span><span class="va">imputed</span><span class="op">$</span><span class="va">Ozone</span></span>
-<span><span class="va">aq_nab</span><span class="op">$</span><span class="va">Solar.R</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html" class="external-link">is.na</a></span><span class="op">(</span><span class="va">aq_nab</span><span class="op">$</span><span class="va">Solar.R</span><span class="op">)</span><span class="op">]</span> <span class="op">&lt;-</span> <span class="va">aq_imp</span><span class="op">$</span><span class="va">imputed</span><span class="op">$</span><span class="va">Solar.R</span></span></code></pre></div>
-<p>In the future there will be a more concise way to insert these
-imputed values into data, but for the moment the method above is what I
-would recommend for single imputation.</p>
-<p>We can then explore the imputed values like so:</p>
-<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">aq_nab</span>,</span>
-<span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Ozone</span>,</span>
-<span>           y <span class="op">=</span> <span class="va">Solar.R</span>,</span>
-<span>           colour <span class="op">=</span> <span class="va">any_missing</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_point.html" class="external-link">geom_point</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-<p><img src="exploring-imputed-values_files/figure-html/hmisc-aregimpute-vis-1.png" width="700"></p>
-</div>
-</div>
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-      <img src="../logo.png" class="logo" alt=""><h1>Getting Started with naniar</h1>
-                        <h4 data-toc-skip class="author">Nicholas
-Tierney</h4>
-            
-            <h4 data-toc-skip class="date">2023-05-01</h4>
-      
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/vignettes/getting-started-w-naniar.Rmd" class="external-link"><code>vignettes/getting-started-w-naniar.Rmd</code></a></small>
-      <div class="d-none name"><code>getting-started-w-naniar.Rmd</code></div>
-    </div>
-
-    
-    
-<div class="section level2">
-<h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
-</h2>
-<p>Missing values are ubiquitous in data and need to be carefully
-explored and handled in the initial stages of analysis. In this vignette
-we describe the tools in the package <code>naniar</code> for exploring
-missing data structures with minimal deviation from the common workflows
-of ggplot and tidy data (<a href="https://www.jstatsoft.org/article/view/v059i10" class="external-link">Wickham, 2014</a>,
-<a href="https://link.springer.com/book/10.1007/978-0-387-98141-3" class="external-link">Wickham,
-2009</a>).</p>
-<p>Sometimes researchers or analysts will introduce or describe a
-mechanism for missingness. For example, they might explain that data
-from a weather station might have a malfunction when there are extreme
-weather events, and does not record temperature data when gusts speeds
-are high. This seems like a nice simple, logical explanation. However,
-like all good explanations, this one is simple, but the process to get
-there was probably not, and likely involved more time than you would
-have liked developing exploratory data analyses and models.</p>
-<p>So when someone presents a really nice plot and a nice sensible
-explanation, the initial thought might be:</p>
-<blockquote>
-<p>They worked it out themselves so quickly, so easy!</p>
-</blockquote>
-<p>As if the problem was so easy to solve, they could
-<em>accidentally</em> solve it - they couldn’t not solve it.</p>
-<p>However, I think that if you manage to get that on the first go, that
-is more like turning around and throwing a rock into a lake and it
-landing in a cup in a boat. Unlikely.</p>
-<p>With that thought in mind, this vignette aims to work with the
-following three questions, using the tools developed in
-<code>naniar</code> and another package, <code>visdat</code>. Namely,
-how do we:</p>
-<ol style="list-style-type: decimal">
-<li>Start looking at missing data?</li>
-<li>Explore missingness mechanisms?</li>
-<li>Model missingness?</li>
-</ol>
-</div>
-<div class="section level2">
-<h2 id="how-do-we-start-looking-at-missing-data">How do we start looking at missing data?<a class="anchor" aria-label="anchor" href="#how-do-we-start-looking-at-missing-data"></a>
-</h2>
-<p>When you start with a dataset, you might do something where you look
-at the general summary, using functions such as:</p>
-<ul>
-<li><code><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary()</a></code></li>
-<li><code><a href="https://rdrr.io/r/utils/str.html" class="external-link">str()</a></code></li>
-<li>
-<a href="https://github.com/ropensci/skimr" class="external-link"><code>skimr::skim</code></a>,
-or</li>
-<li><code><a href="https://pillar.r-lib.org/reference/glimpse.html" class="external-link">dplyr::glimpse()</a></code></li>
-</ul>
-<p>These works really well when you’ve got a small amount of data, but
-when you have more data, you are generally limited by how much you can
-read.</p>
-<p>So before you start looking at missing data, you’ll need to look at
-the data, but what does that even mean?</p>
-<p>The package <code>visdat</code> helps you get a handle on this.
-<code>visdat</code> provides a visualisation of an entire data frame at
-once, and was heavily inspired by <a href="https://setosa.io/blog/2014/08/03/csv-fingerprints/" class="external-link"><code>csv-fingerprint</code></a>,
-and functions like <code>missmap</code>, from <code>Amelia</code>.</p>
-<p>There are two main functions in the <code>visdat</code> package:</p>
-<ul>
-<li>
-<code>vis_dat</code>, and</li>
-<li><code>vis_miss</code></li>
-</ul>
-<div class="section level3">
-<h3 id="vis_dat">
-<code>vis_dat</code><a class="anchor" aria-label="anchor" href="#vis_dat"></a>
-</h3>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://docs.ropensci.org/visdat/" class="external-link">visdat</a></span><span class="op">)</span></span>
-<span><span class="fu"><a href="https://docs.ropensci.org/visdat/reference/vis_dat.html" class="external-link">vis_dat</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></code></pre></div>
-<p><img src="getting-started-w-naniar_files/figure-html/vis-dat-1.png" width="500" style="display: block; margin: auto;"></p>
-<p><code>vis_dat</code> visualises the whole dataframe at once, and
-provides information about the class of the data input into R, as well
-as whether the data is missing or not.</p>
-<div class="section level4">
-<h4 id="vis_miss">
-<code>vis_miss</code><a class="anchor" aria-label="anchor" href="#vis_miss"></a>
-</h4>
-<p>The function <code>vis_miss</code> provides a summary of whether the
-data is missing or not. It also provides the amount of missings in each
-columns.</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="https://docs.ropensci.org/visdat/reference/vis_miss.html" class="external-link">vis_miss</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></code></pre></div>
-<p><img src="getting-started-w-naniar_files/figure-html/vis-miss-cluster-vanilla-1.png" width="500" style="display: block; margin: auto;"></p>
-<p>So here, Ozone and Solar.R have the most missing data, with Ozone
-having 24.2% missing data and Solar.R have 4.6%. The other variables do
-not have any missing data.</p>
-<p>To read more about the functions available in <code>visdat</code> see
-the vignette <a href="https://CRAN.R-project.org/package=visdat/vignettes/using_visdat.html" class="external-link">“Using
-visdat”</a></p>
-</div>
-</div>
-</div>
-<div class="section level2">
-<h2 id="exploring-missingness-relationships">Exploring missingness relationships<a class="anchor" aria-label="anchor" href="#exploring-missingness-relationships"></a>
-</h2>
-<p>We can identify key variables that are missing using
-<code>vis_miss</code>, but for further exploration, we need to explore
-the relationship amongst the variables in this data:</p>
-<ul>
-<li>Ozone,</li>
-<li>Solar.R</li>
-<li>Wind</li>
-<li>Temp</li>
-<li>Month</li>
-<li>Day</li>
-</ul>
-<p>Typically, when exploring this data, you might want to explore the
-variables Solar.R and Ozone, and so plot a scatterplot of solar
-radiation and ozone, doing something like this:</p>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span>
-<span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">airquality</span>, </span>
-<span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Solar.R</span>, </span>
-<span>           y <span class="op">=</span> <span class="va">Ozone</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_point.html" class="external-link">geom_point</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## Warning: Removed 42 rows containing missing values (`geom_point()`).</span></span></code></pre>
-<p><img src="getting-started-w-naniar_files/figure-html/example-geom-point-1.png" width="500" style="display: block; margin: auto;"></p>
-<p>The problem with this is that ggplot does not handle missings be
-default, and removes the missing values. This makes them hard to
-explore. It also presents the strange question of “how do you visualise
-something that is not there?”. One approach to visualising missing data
-comes from <a href="https://en.wikipedia.org/wiki/GGobi" class="external-link"><code>ggobi</code></a> and <a href="http://www.rosuda.org/MANET/" class="external-link"><code>manet</code></a>, where we
-replace “NA” values with values 10% lower than the minimum value in that
-variable.</p>
-<p>This process is performed and visualised for you with the
-<code><a href="../reference/geom_miss_point.html">geom_miss_point()</a></code> ggplot2 geom. Here, we illustrate by
-exploring the relationship between Ozone and Solar radiation from the
-airquality dataset.</p>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">airquality</span>, </span>
-<span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Solar.R</span>, </span>
-<span>           y <span class="op">=</span> <span class="va">Ozone</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_point.html" class="external-link">geom_point</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## Warning: Removed 42 rows containing missing values (`geom_point()`).</span></span></code></pre>
-<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/njtierney/naniar" class="external-link">naniar</a></span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">airquality</span>, </span>
-<span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Solar.R</span>, </span>
-<span>           y <span class="op">=</span> <span class="va">Ozone</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="../reference/geom_miss_point.html">geom_miss_point</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-<p><img src="getting-started-w-naniar_files/figure-html/geom-miss-point-1.png" width="50%" style="display: block; margin: auto;"><img src="getting-started-w-naniar_files/figure-html/geom-miss-point-2.png" width="50%" style="display: block; margin: auto;"></p>
-<p>Being a proper ggplot geom, it supports all of the standard features
-of ggplot2, such as <strong>facets</strong>,</p>
-<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">airquality</span>, </span>
-<span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Solar.R</span>, </span>
-<span>           y <span class="op">=</span> <span class="va">Ozone</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="../reference/geom_miss_point.html">geom_miss_point</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/facet_wrap.html" class="external-link">facet_wrap</a></span><span class="op">(</span><span class="op">~</span><span class="va">Month</span><span class="op">)</span></span></code></pre></div>
-<p><img src="getting-started-w-naniar_files/figure-html/ggmissing-facet-1.png" width="70%" style="display: block; margin: auto;"></p>
-<p>And different <strong>themes</strong></p>
-<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">airquality</span>, </span>
-<span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Solar.R</span>, </span>
-<span>           y <span class="op">=</span> <span class="va">Ozone</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="../reference/geom_miss_point.html">geom_miss_point</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/facet_wrap.html" class="external-link">facet_wrap</a></span><span class="op">(</span><span class="op">~</span><span class="va">Month</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_dark</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-<p><img src="getting-started-w-naniar_files/figure-html/ggmissing-theme-1.png" width="70%" style="display: block; margin: auto;"></p>
-<div class="section level3">
-<h3 id="visualising-missings-in-variables">Visualising missings in variables<a class="anchor" aria-label="anchor" href="#visualising-missings-in-variables"></a>
-</h3>
-<p>Another approach to visualising the missings in a dataset is to use
-the <code>gg_miss_var</code> plot:</p>
-<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/gg_miss_var.html">gg_miss_var</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></code></pre></div>
-<p><img src="getting-started-w-naniar_files/figure-html/gg-miss-var-1.png" width="500" style="display: block; margin: auto;"></p>
-<p>The plots created with the <code>gg_miss</code> family all have a
-basic theme, but you can customise them, and add arguments like so:</p>
-<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/gg_miss_var.html">gg_miss_var</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span> <span class="op">+</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_bw</a></span><span class="op">(</span><span class="op">)</span> </span></code></pre></div>
-<p><img src="getting-started-w-naniar_files/figure-html/gg-miss-var-theme-1.png" width="500" style="display: block; margin: auto;"></p>
-<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/gg_miss_var.html">gg_miss_var</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span> <span class="op">+</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span>y <span class="op">=</span> <span class="st">"Look at all the missing ones"</span><span class="op">)</span></span></code></pre></div>
-<p><img src="getting-started-w-naniar_files/figure-html/gg-miss-var-theme-2.png" width="500" style="display: block; margin: auto;"></p>
-<p>To add facets in these plots, you can use the <code>facet</code>
-argument:</p>
-<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/gg_miss_var.html">gg_miss_var</a></span><span class="op">(</span><span class="va">airquality</span>, facet <span class="op">=</span> <span class="va">Month</span><span class="op">)</span></span></code></pre></div>
-<p><img src="getting-started-w-naniar_files/figure-html/gg-miss-var-facet-1.png" width="500" style="display: block; margin: auto;"></p>
-<p>There are more visualisations available in <code>naniar</code> (each
-starting with <code>gg_miss_</code>) - you can see these in the <a href="https://cran.r-project.org/package=naniar/vignettes/naniar-visualisation.html" class="external-link">“Gallery
-of Missing Data Visualisations” vignette.</a>.</p>
-<p>It is important to note that for every visualisation of missing data
-in <code>naniar</code>, there is an accompanying function to get the
-dataframe of the plot out. This is important as the plot should not
-return a dataframe - but we also need to make the data available for use
-by the user so that it isn’t locked into a plot. You can find these
-summary plots below, with <code>miss_var_summary</code> providing the
-dataframe that <code><a href="../reference/gg_miss_var.html">gg_miss_var()</a></code> is based on.</p>
-</div>
-</div>
-<div class="section level2">
-<h2 id="replacing-existing-values-with-na">Replacing existing values with NA<a class="anchor" aria-label="anchor" href="#replacing-existing-values-with-na"></a>
-</h2>
-<p>When you are dealing with missing values, you might want to replace
-values with a missing values (NA). This is useful in cases when you know
-the origin of the data and can be certain which values should be
-missing. For example, you might know that all values of “N/A”, “N A”,
-and “Not Available”, or -99, or -1 are supposed to be missing.</p>
-<p><code>naniar</code> provides functions to specifically work on this
-type of problem using the function <code>replace_with_na</code>. This
-function is the compliment to <code><a href="https://tidyr.tidyverse.org/reference/replace_na.html" class="external-link">tidyr::replace_na</a></code>, which
-replaces an NA value with a specified value, whereas
-<code><a href="../reference/replace_with_na.html">naniar::replace_with_na</a></code> replaces a value with an NA:</p>
-<ul>
-<li>
-<code><a href="https://tidyr.tidyverse.org/reference/replace_na.html" class="external-link">tidyr::replace_na</a></code>: Missing values turns into a value
-(NA –&gt; -99)</li>
-<li>
-<code><a href="../reference/replace_with_na.html">naniar::replace_with_na</a></code>: Value becomes a missing value
-(-99 –&gt; NA)</li>
-</ul>
-<p>You can read more about this in the vignette <a href="http://naniar.njtierney.com/articles/replace-with-na.html">“Replacing
-values with NA”</a></p>
-</div>
-<div class="section level2">
-<h2 id="tidy-missing-data-the-shadow-matrix">Tidy Missing Data: The Shadow Matrix<a class="anchor" aria-label="anchor" href="#tidy-missing-data-the-shadow-matrix"></a>
-</h2>
-<p>Representing missing data structure in a tidy format is achieved
-using the shadow matrix, introduced in <a href="https://www.researchgate.net/publication/2758672_Missing_Data_in_Interactive_High-Dimensional_Data_Visualization" class="external-link">Swayne
-and Buja</a>. The shadow matrix is the same dimension as the data, and
-consists of binary indicators of missingness of data values, where
-missing is represented as “NA”, and not missing is represented as “!NA”.
-Although these may be represented as 1 and 0, respectively. This
-representation can be seen in the figure below, adding the suffix “_NA”
-to the variables. This structure can also be extended to allow for
-additional factor levels to be created. For example 0 indicates data
-presence, 1 indicates missing values, 2 indicates imputed value, and 3
-might indicate a particular type or class of missingness, where reasons
-for missingness might be known or inferred. The data matrix can also be
-augmented to include the shadow matrix, which facilitates visualisation
-of univariate and bivariate missing data visualisations. Another format
-is to display it in long form, which facilitates heatmap style
-visualisations. This approach can be very helpful for giving an overview
-of which variables contain the most missingness. Methods can also be
-applied to rearrange rows and columns to find clusters, and identify
-other interesting features of the data that may have previously been
-hidden or unclear.</p>
-<p><img src="missingness-data-structures.png" width="800px" style="display: block; margin: auto;"></p>
-<p><strong>Illustration of data structures for facilitating
-visualisation of missings and not missings</strong></p>
-<p>The <code>shadow</code> functions provide a way to keep track of
-missing values. The <code>as_shadow</code> function creates a dataframe
-with the same set of columns, but with the column names added a suffix
-<code>_NA</code></p>
-<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/as_shadow.html">as_shadow</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## <span style="color: #949494;"># A tibble: 153 × 6</span></span></span>
-<span><span class="co">##    Ozone_NA Solar.R_NA Wind_NA Temp_NA Month_NA Day_NA</span></span>
-<span><span class="co">##    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span> </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 1</span> !NA      !NA        !NA     !NA     !NA      !NA   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 2</span> !NA      !NA        !NA     !NA     !NA      !NA   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 3</span> !NA      !NA        !NA     !NA     !NA      !NA   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 4</span> !NA      !NA        !NA     !NA     !NA      !NA   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 5</span> NA       NA         !NA     !NA     !NA      !NA   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 6</span> !NA      NA         !NA     !NA     !NA      !NA   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 7</span> !NA      !NA        !NA     !NA     !NA      !NA   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 8</span> !NA      !NA        !NA     !NA     !NA      !NA   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 9</span> !NA      !NA        !NA     !NA     !NA      !NA   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">10</span> NA       !NA        !NA     !NA     !NA      !NA   </span></span>
-<span><span class="co">## <span style="color: #949494;"># ℹ 143 more rows</span></span></span></code></pre>
-<p><code>bind_shadow</code> attaches a shadow to the current dataframe,
-a format we call “nabular”, a portmanteau of <code>NA</code> a
-<code>tabular</code>. You can also use <code>nabular</code> to do the
-same thing:</p>
-<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">aq_shadow</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/bind_shadow.html">bind_shadow</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span>
-<span><span class="va">aq_nab</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/nabular.html">nabular</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span>
-<span></span>
-<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## </span></span>
-<span><span class="co">## Attaching package: 'dplyr'</span></span></code></pre>
-<pre><code><span><span class="co">## The following objects are masked from 'package:stats':</span></span>
-<span><span class="co">## </span></span>
-<span><span class="co">##     filter, lag</span></span></code></pre>
-<pre><code><span><span class="co">## The following objects are masked from 'package:base':</span></span>
-<span><span class="co">## </span></span>
-<span><span class="co">##     intersect, setdiff, setequal, union</span></span></code></pre>
-<div class="sourceCode" id="cb20"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="https://pillar.r-lib.org/reference/glimpse.html" class="external-link">glimpse</a></span><span class="op">(</span><span class="va">aq_shadow</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## Rows: 153</span></span>
-<span><span class="co">## Columns: 12</span></span>
-<span><span class="co">## $ Ozone      <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> 41, 36, 12, 18, NA, 28, 23, 19, 8, NA, 7, 16, 11, 14, 18, 1…</span></span>
-<span><span class="co">## $ Solar.R    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> 190, 118, 149, 313, NA, NA, 299, 99, 19, 194, NA, 256, 290,…</span></span>
-<span><span class="co">## $ Wind       <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> 7.4, 8.0, 12.6, 11.5, 14.3, 14.9, 8.6, 13.8, 20.1, 8.6, 6.9…</span></span>
-<span><span class="co">## $ Temp       <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> 67, 72, 74, 62, 56, 66, 65, 59, 61, 69, 74, 69, 66, 68, 58,…</span></span>
-<span><span class="co">## $ Month      <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,…</span></span>
-<span><span class="co">## $ Day        <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, …</span></span>
-<span><span class="co">## $ Ozone_NA   <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span> !NA, !NA, !NA, !NA, NA, !NA, !NA, !NA, !NA, NA, !NA, !NA, !…</span></span>
-<span><span class="co">## $ Solar.R_NA <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span> !NA, !NA, !NA, !NA, NA, NA, !NA, !NA, !NA, !NA, NA, !NA, !N…</span></span>
-<span><span class="co">## $ Wind_NA    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span> !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA,…</span></span>
-<span><span class="co">## $ Temp_NA    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span> !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA,…</span></span>
-<span><span class="co">## $ Month_NA   <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span> !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA,…</span></span>
-<span><span class="co">## $ Day_NA     <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span> !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA,…</span></span></code></pre>
-<div class="sourceCode" id="cb22"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="https://pillar.r-lib.org/reference/glimpse.html" class="external-link">glimpse</a></span><span class="op">(</span><span class="va">aq_nab</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## Rows: 153</span></span>
-<span><span class="co">## Columns: 12</span></span>
-<span><span class="co">## $ Ozone      <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> 41, 36, 12, 18, NA, 28, 23, 19, 8, NA, 7, 16, 11, 14, 18, 1…</span></span>
-<span><span class="co">## $ Solar.R    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> 190, 118, 149, 313, NA, NA, 299, 99, 19, 194, NA, 256, 290,…</span></span>
-<span><span class="co">## $ Wind       <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> 7.4, 8.0, 12.6, 11.5, 14.3, 14.9, 8.6, 13.8, 20.1, 8.6, 6.9…</span></span>
-<span><span class="co">## $ Temp       <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> 67, 72, 74, 62, 56, 66, 65, 59, 61, 69, 74, 69, 66, 68, 58,…</span></span>
-<span><span class="co">## $ Month      <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,…</span></span>
-<span><span class="co">## $ Day        <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, …</span></span>
-<span><span class="co">## $ Ozone_NA   <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span> !NA, !NA, !NA, !NA, NA, !NA, !NA, !NA, !NA, NA, !NA, !NA, !…</span></span>
-<span><span class="co">## $ Solar.R_NA <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span> !NA, !NA, !NA, !NA, NA, NA, !NA, !NA, !NA, !NA, NA, !NA, !N…</span></span>
-<span><span class="co">## $ Wind_NA    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span> !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA,…</span></span>
-<span><span class="co">## $ Temp_NA    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span> !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA,…</span></span>
-<span><span class="co">## $ Month_NA   <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span> !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA,…</span></span>
-<span><span class="co">## $ Day_NA     <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span> !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA,…</span></span></code></pre>
-<div class="sourceCode" id="cb24"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/all.equal.html" class="external-link">all.equal</a></span><span class="op">(</span><span class="va">aq_shadow</span>, <span class="va">aq_nab</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## [1] TRUE</span></span></code></pre>
-<p>Doing this provides a consistent syntax for referring to variables
-with missing values.</p>
-<p><em>Nabular</em> data provides a useful pattern to explore missing
-values, grouping by the missing/complete of one variable and looking at
-the mean and other summary values. Below we show the mean, sd, variance,
-and min and max values of Solar.R for when Ozone is present, and when it
-is missing.</p>
-<div class="sourceCode" id="cb26"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/bind_shadow.html">bind_shadow</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">Ozone_NA</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise_all.html" class="external-link">summarise_at</a></span><span class="op">(</span>.vars <span class="op">=</span> <span class="st">"Solar.R"</span>,</span>
-<span>               .funs <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"mean"</span>, <span class="st">"sd"</span>, <span class="st">"var"</span>, <span class="st">"min"</span>, <span class="st">"max"</span><span class="op">)</span>,</span>
-<span>               na.rm <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## <span style="color: #949494;"># A tibble: 2 × 6</span></span></span>
-<span><span class="co">##   Ozone_NA  mean    sd   var   min   max</span></span>
-<span><span class="co">##   <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">1</span> !NA       185.  91.2 <span style="text-decoration: underline;">8</span>309.     7   334</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">2</span> NA        190.  87.7 <span style="text-decoration: underline;">7</span>690.    31   332</span></span></code></pre>
-<p>Below, we can plot the distribution of Temperature, plotting for
-values of temperature when Ozone is missing, and when it is not
-missing.</p>
-<div class="sourceCode" id="cb28"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">aq_shadow</span>,</span>
-<span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Temp</span>,</span>
-<span>           colour <span class="op">=</span> <span class="va">Ozone_NA</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_density.html" class="external-link">geom_density</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-<p><img src="getting-started-w-naniar_files/figure-html/shadow-plot-1.png" width="60%" style="display: block; margin: auto;"></p>
-<p>We can also explore the value of air temperature and humidity based
-on missingness of each.</p>
-<div class="sourceCode" id="cb29"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="co"># what if we explore the value of air temperature and humidity based on</span></span>
-<span><span class="co"># the missingness of each</span></span>
-<span>  <span class="va">oceanbuoys</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>    <span class="fu"><a href="../reference/bind_shadow.html">bind_shadow</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">air_temp_c</span>,</span>
-<span>               fill <span class="op">=</span> <span class="va">humidity_NA</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
-<span>        <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_histogram.html" class="external-link">geom_histogram</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.</span></span></code></pre>
-<pre><code><span><span class="co">## Warning: Removed 81 rows containing non-finite values (`stat_bin()`).</span></span></code></pre>
-<p><img src="getting-started-w-naniar_files/figure-html/temp-humidity-explore-1.png" width="500" style="display: block; margin: auto;"></p>
-<div class="sourceCode" id="cb32"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span>  <span class="va">oceanbuoys</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>    <span class="fu"><a href="../reference/bind_shadow.html">bind_shadow</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">humidity</span>,</span>
-<span>               fill <span class="op">=</span> <span class="va">air_temp_c_NA</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
-<span>        <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_histogram.html" class="external-link">geom_histogram</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.</span></span></code></pre>
-<pre><code><span><span class="co">## Warning: Removed 93 rows containing non-finite values (`stat_bin()`).</span></span></code></pre>
-<p><img src="getting-started-w-naniar_files/figure-html/temp-humidity-explore-2.png" width="500" style="display: block; margin: auto;"></p>
-<p>Binding the shadow here also has great benefits when combined with
-imputation.</p>
-</div>
-<div class="section level2">
-<h2 id="visualising-imputed-values">Visualising imputed values<a class="anchor" aria-label="anchor" href="#visualising-imputed-values"></a>
-</h2>
-<p>With the easy-to-use <a href="https://cran.r-project.org/package=simputation" class="external-link"><code>simputation</code></a>
-package, we impute values for Ozone, then visualise the data:</p>
-<div class="sourceCode" id="cb35"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/markvanderloo/simputation" class="external-link">simputation</a></span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## </span></span>
-<span><span class="co">## Attaching package: 'simputation'</span></span></code></pre>
-<pre><code><span><span class="co">## The following object is masked from 'package:naniar':</span></span>
-<span><span class="co">## </span></span>
-<span><span class="co">##     impute_median</span></span></code></pre>
-<div class="sourceCode" id="cb38"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span>
-<span></span>
-<span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/pkg/simputation/man/impute_lm.html" class="external-link">impute_lm</a></span><span class="op">(</span><span class="va">Ozone</span> <span class="op">~</span> <span class="va">Temp</span> <span class="op">+</span> <span class="va">Wind</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Temp</span>,</span>
-<span>             y <span class="op">=</span> <span class="va">Ozone</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_point.html" class="external-link">geom_point</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-<p><img src="getting-started-w-naniar_files/figure-html/simpute-invisible-1.png" width="500" style="display: block; margin: auto;"></p>
-<p>Note that we no longer get any errors regarding missing observations
-- because they are all imputed! But this comes at a cost: we also no
-longer have information about where the imputations are - they are now
-sort of invisible.</p>
-<p>Using the shadow matrix to keep track of where the missings are, you
-can actually keep track of the imputations, by colouring by what was
-previously missing in Ozone.</p>
-<div class="sourceCode" id="cb39"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">aq_shadow</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/r/base/as.data.frame.html" class="external-link">as.data.frame</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> </span>
-<span>  <span class="fu"><a href="https://rdrr.io/pkg/simputation/man/impute_lm.html" class="external-link">impute_lm</a></span><span class="op">(</span><span class="va">Ozone</span> <span class="op">~</span> <span class="va">Temp</span> <span class="op">+</span> <span class="va">Wind</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Temp</span>,</span>
-<span>             y <span class="op">=</span> <span class="va">Ozone</span>,</span>
-<span>             colour <span class="op">=</span> <span class="va">Ozone_NA</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_point.html" class="external-link">geom_point</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-<p><img src="getting-started-w-naniar_files/figure-html/simpute-visible-1.png" width="500" style="display: block; margin: auto;"></p>
-<div class="section level3">
-<h3 id="numerical-summaries-of-missing-values">Numerical summaries of missing values<a class="anchor" aria-label="anchor" href="#numerical-summaries-of-missing-values"></a>
-</h3>
-<p><code>naniar</code> also provide numerical summaries for missing
-data. Two convenient counters of complete values and missings are
-<code><a href="../reference/n_miss.html">n_miss()</a></code> and <code><a href="../reference/n_complete.html">n_complete()</a></code>. These work on both
-dataframes and vectors, similar to <code><a href="https://dplyr.tidyverse.org/reference/n_distinct.html" class="external-link">dplyr::n_distinct()</a></code></p>
-<div class="sourceCode" id="cb40"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/n_distinct.html" class="external-link">n_distinct</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## [1] 153</span></span></code></pre>
-<div class="sourceCode" id="cb42"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/n_distinct.html" class="external-link">n_distinct</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">$</span><span class="va">Ozone</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## [1] 68</span></span></code></pre>
-<div class="sourceCode" id="cb44"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/n_miss.html">n_miss</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## [1] 44</span></span></code></pre>
-<div class="sourceCode" id="cb46"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/n_miss.html">n_miss</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">$</span><span class="va">Ozone</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## [1] 37</span></span></code></pre>
-<div class="sourceCode" id="cb48"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/n_complete.html">n_complete</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## [1] 874</span></span></code></pre>
-<div class="sourceCode" id="cb50"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/n_complete.html">n_complete</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">$</span><span class="va">Ozone</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## [1] 116</span></span></code></pre>
-<p>The syntax for the other numerical sumamries in <code>naniar</code>
-are <code>miss_</code>, and then <code>case</code>, or <code>var</code>
-to refer to cases or variables. There are then <code>summary</code>,
-<code>table</code>, <code>run</code>, <code>span</code>, and
-<code>cumsum</code> options to explore missing data.</p>
-<p><code>prop_miss_case</code> and <code>pct_miss_case</code> return
-numeric value describing the proportion or percent of missing values in
-the dataframe.</p>
-<div class="sourceCode" id="cb52"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/prop-miss-complete-case.html">prop_miss_case</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## [1] 0.2745098</span></span></code></pre>
-<div class="sourceCode" id="cb54"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/pct-miss-complete-case.html">pct_miss_case</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## [1] 27.45098</span></span></code></pre>
-<p><code><a href="../reference/miss_case_summary.html">miss_case_summary()</a></code> returns a numeric value that
-describes the number of missings in a given case (aka row), the percent
-of missings in that row.</p>
-<div class="sourceCode" id="cb56"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/miss_case_summary.html">miss_case_summary</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## <span style="color: #949494;"># A tibble: 153 × 3</span></span></span>
-<span><span class="co">##     case n_miss pct_miss</span></span>
-<span><span class="co">##    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 1</span>     5      2     33.3</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 2</span>    27      2     33.3</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 3</span>     6      1     16.7</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 4</span>    10      1     16.7</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 5</span>    11      1     16.7</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 6</span>    25      1     16.7</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 7</span>    26      1     16.7</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 8</span>    32      1     16.7</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 9</span>    33      1     16.7</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">10</span>    34      1     16.7</span></span>
-<span><span class="co">## <span style="color: #949494;"># ℹ 143 more rows</span></span></span></code></pre>
-<p><code><a href="../reference/miss_case_table.html">miss_case_table()</a></code> tabulates the number of missing values
-in a case / row. Below, this shows the number of missings in a case:</p>
-<ul>
-<li>There are 111 cases with 0 missings, which comprises about 72% of
-the data.</li>
-<li>There are then 40 cases with 1 missing, these make up 26% of the
-data.</li>
-<li>There are then 2 cases with 2 missing - these make up 1% of the
-data.</li>
-</ul>
-<div class="sourceCode" id="cb58"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/miss_case_table.html">miss_case_table</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## <span style="color: #949494;"># A tibble: 3 × 3</span></span></span>
-<span><span class="co">##   n_miss_in_case n_cases pct_cases</span></span>
-<span><span class="co">##            <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">1</span>              0     111     72.5 </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">2</span>              1      40     26.1 </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">3</span>              2       2      1.31</span></span></code></pre>
-<p>Similar to <code><a href="../reference/pct-miss-complete-case.html">pct_miss_case()</a></code>,
-<code><a href="../reference/prop-miss-complete-case.html">prop_miss_case()</a></code>, <code><a href="../reference/pct-miss-complete-var.html">pct_miss_var()</a></code> and
-<code><a href="../reference/prop-miss-complete-var.html">prop_miss_var()</a></code> returns the percent and proportion of
-variables that contain a missing value.</p>
-<div class="sourceCode" id="cb60"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/prop-miss-complete-var.html">prop_miss_var</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## [1] 0.3333333</span></span></code></pre>
-<div class="sourceCode" id="cb62"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/pct-miss-complete-var.html">pct_miss_var</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## [1] 33.33333</span></span></code></pre>
-<p><code><a href="../reference/miss_var_summary.html">miss_var_summary()</a></code> then returns the number of missing
-values in a variable, and the percent missing in that variable.</p>
-<div class="sourceCode" id="cb64"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/miss_var_summary.html">miss_var_summary</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## <span style="color: #949494;"># A tibble: 6 × 3</span></span></span>
-<span><span class="co">##   variable n_miss pct_miss</span></span>
-<span><span class="co">##   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">1</span> Ozone        37    24.2 </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">2</span> Solar.R       7     4.58</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">3</span> Wind          0     0   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">4</span> Temp          0     0   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">5</span> Month         0     0   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">6</span> Day           0     0</span></span></code></pre>
-<p>Finally, <code><a href="../reference/miss_var_table.html">miss_var_table()</a></code>. This describes the number of
-missings in a variable.</p>
-<ul>
-<li>There are 4 variables with 0 missings, comprising 66.67% of
-variables in the dataset.</li>
-<li>There is 1 variable with 7 missings</li>
-<li>There is 1 variable with 37 missings</li>
-</ul>
-<div class="sourceCode" id="cb66"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/miss_var_table.html">miss_var_table</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## <span style="color: #949494;"># A tibble: 3 × 3</span></span></span>
-<span><span class="co">##   n_miss_in_var n_vars pct_vars</span></span>
-<span><span class="co">##           <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">1</span>             0      4     66.7</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">2</span>             7      1     16.7</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">3</span>            37      1     16.7</span></span></code></pre>
-<p>There are also summary functions for exploring missings that occur
-over a particular span or period of the dataset, or the number of
-missings in a single run:</p>
-<ul>
-<li>
-<code><a href="../reference/miss_var_run.html">miss_var_run()</a></code>, and</li>
-<li><code><a href="../reference/miss_var_span.html">miss_var_span()</a></code></li>
-</ul>
-<p><code><a href="../reference/miss_var_run.html">miss_var_run()</a></code> can be particularly useful in time series
-data, as it allows you to provide summaries for the number of missings
-or complete values in a single run. The function
-<code><a href="../reference/miss_var_run.html">miss_var_run()</a></code> provides a data.frame of the run length of
-missings and complete values. To explore this function we will use the
-built-in dataset, <code>pedestrian</code>, which contains hourly counts
-of pedestrians from four locations around Melbourne, Australia, from
-2016.</p>
-<p>To use <code><a href="../reference/miss_var_run.html">miss_var_run()</a></code>, you specify the variable that you
-want to explore the runs of missingness for, in this case,
-<code>hourly_counts</code>:</p>
-<div class="sourceCode" id="cb68"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/miss_var_run.html">miss_var_run</a></span><span class="op">(</span><span class="va">pedestrian</span>,</span>
-<span>             <span class="va">hourly_counts</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## <span style="color: #949494;"># A tibble: 35 × 2</span></span></span>
-<span><span class="co">##    run_length is_na   </span></span>
-<span><span class="co">##         <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 1</span>       <span style="text-decoration: underline;">6</span>628 complete</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 2</span>          1 missing </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 3</span>       <span style="text-decoration: underline;">5</span>250 complete</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 4</span>        624 missing </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 5</span>       <span style="text-decoration: underline;">3</span>652 complete</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 6</span>          1 missing </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 7</span>       <span style="text-decoration: underline;">1</span>290 complete</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 8</span>        744 missing </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 9</span>       <span style="text-decoration: underline;">7</span>420 complete</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">10</span>          1 missing </span></span>
-<span><span class="co">## <span style="color: #949494;"># ℹ 25 more rows</span></span></span></code></pre>
-<p><code><a href="../reference/miss_var_span.html">miss_var_span()</a></code> is used to determine the number of
-missings over a specified repeating span of rows in variable of a
-dataframe. Similar to <code><a href="../reference/miss_var_run.html">miss_var_run()</a></code>, you specify the
-variable that you wish to explore, you then also specify the size of the
-span with the <code>span_every</code> argument.</p>
-<div class="sourceCode" id="cb70"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/miss_var_span.html">miss_var_span</a></span><span class="op">(</span><span class="va">pedestrian</span>,</span>
-<span>              <span class="va">hourly_counts</span>,</span>
-<span>              span_every <span class="op">=</span> <span class="fl">100</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## <span style="color: #949494;"># A tibble: 377 × 6</span></span></span>
-<span><span class="co">##    span_counter n_miss n_complete prop_miss prop_complete n_in_span</span></span>
-<span><span class="co">##           <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 1</span>            1      0        100         0             1       100</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 2</span>            2      0        100         0             1       100</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 3</span>            3      0        100         0             1       100</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 4</span>            4      0        100         0             1       100</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 5</span>            5      0        100         0             1       100</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 6</span>            6      0        100         0             1       100</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 7</span>            7      0        100         0             1       100</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 8</span>            8      0        100         0             1       100</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 9</span>            9      0        100         0             1       100</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">10</span>           10      0        100         0             1       100</span></span>
-<span><span class="co">## <span style="color: #949494;"># ℹ 367 more rows</span></span></span></code></pre>
-</div>
-</div>
-<div class="section level2">
-<h2 id="using-group_by-with-naniar">Using <code>group_by</code> with naniar<a class="anchor" aria-label="anchor" href="#using-group_by-with-naniar"></a>
-</h2>
-<p>Every <code>miss_*</code> summary function that returns a dataframe
-can be used with dplyr <code><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by()</a></code>. For example, if you
-would like to look at the number of missing values for all variables of
-pedestrian data.</p>
-<div class="sourceCode" id="cb72"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">pedestrian</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu"><a href="../reference/miss_var_summary.html">miss_var_summary</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## <span style="color: #949494;"># A tibble: 9 × 3</span></span></span>
-<span><span class="co">##   variable      n_miss pct_miss</span></span>
-<span><span class="co">##   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>          <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">1</span> hourly_counts   <span style="text-decoration: underline;">2</span>548     6.76</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">2</span> date_time          0     0   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">3</span> year               0     0   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">4</span> month              0     0   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">5</span> month_day          0     0   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">6</span> week_day           0     0   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">7</span> hour               0     0   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">8</span> sensor_id          0     0   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">9</span> sensor_name        0     0</span></span></code></pre>
-<p>We see that this is in <code>hourly_counts</code>. We can then
-explore this by month, and filder by the variable being
-<code>hourly_counts</code>, since it is the only one with missing
-values.</p>
-<div class="sourceCode" id="cb74"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">pedestrian</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">month</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span> <span class="fu"><a href="../reference/miss_var_summary.html">miss_var_summary</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">variable</span> <span class="op">==</span> <span class="st">"hourly_counts"</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## <span style="color: #949494;"># A tibble: 12 × 4</span></span></span>
-<span><span class="co">## <span style="color: #949494;"># Groups:   month [12]</span></span></span>
-<span><span class="co">##    month     variable      n_miss pct_miss</span></span>
-<span><span class="co">##    <span style="color: #949494; font-style: italic;">&lt;ord&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>          <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 1</span> January   hourly_counts      0     0   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 2</span> February  hourly_counts      0     0   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 3</span> March     hourly_counts      0     0   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 4</span> April     hourly_counts    552    19.2 </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 5</span> May       hourly_counts     72     2.42</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 6</span> June      hourly_counts      0     0   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 7</span> July      hourly_counts      0     0   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 8</span> August    hourly_counts    408    13.7 </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 9</span> September hourly_counts      0     0   </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">10</span> October   hourly_counts    412     7.44</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">11</span> November  hourly_counts    888    30.8 </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">12</span> December  hourly_counts    216     7.26</span></span></code></pre>
-</div>
-<div class="section level2">
-<h2 id="modelling-missingness">Modelling missingness<a class="anchor" aria-label="anchor" href="#modelling-missingness"></a>
-</h2>
-<p>The final question we proposed in this vignette was:</p>
-<ol start="3" style="list-style-type: decimal">
-<li>Can we model missingness?</li>
-</ol>
-<p>Sometimes it can be impractical to explore all of the variables that
-have missing data. One approach, however, is to model missing data using
-methods from Tierney et el. (2015).</p>
-<p>Here, the approach is to predict the proportion of missingness in a
-given case, using all variables. There is a little helper function to
-add a column with the proportion of cases or rows missing -
-<code><a href="../reference/add_prop_miss.html">add_prop_miss()</a></code>. This created a column named “prop_miss”,
-which is the proportion of missing values in that row.</p>
-<div class="sourceCode" id="cb76"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/add_prop_miss.html">add_prop_miss</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">##   Ozone Solar.R Wind Temp Month Day prop_miss_all</span></span>
-<span><span class="co">## 1    41     190  7.4   67     5   1     0.0000000</span></span>
-<span><span class="co">## 2    36     118  8.0   72     5   2     0.0000000</span></span>
-<span><span class="co">## 3    12     149 12.6   74     5   3     0.0000000</span></span>
-<span><span class="co">## 4    18     313 11.5   62     5   4     0.0000000</span></span>
-<span><span class="co">## 5    NA      NA 14.3   56     5   5     0.3333333</span></span>
-<span><span class="co">## 6    28      NA 14.9   66     5   6     0.1666667</span></span></code></pre>
-<p>We can then use a model like decision trees to predict which
-variables and their values are important for predicting the proportion
-of missingness:</p>
-<div class="sourceCode" id="cb78"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/bethatkinson/rpart" class="external-link">rpart</a></span><span class="op">)</span></span>
-<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="http://www.milbo.org/rpart-plot/index.html" class="external-link">rpart.plot</a></span><span class="op">)</span></span>
-<span></span>
-<span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/add_prop_miss.html">add_prop_miss</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/pkg/rpart/man/rpart.html" class="external-link">rpart</a></span><span class="op">(</span><span class="va">prop_miss_all</span> <span class="op">~</span> <span class="va">.</span>, data <span class="op">=</span> <span class="va">.</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/pkg/rpart.plot/man/prp.html" class="external-link">prp</a></span><span class="op">(</span>type <span class="op">=</span> <span class="fl">4</span>, extra <span class="op">=</span> <span class="fl">101</span>, prefix <span class="op">=</span> <span class="st">"Prop. Miss = "</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## Warning: Cannot retrieve the data used to build the model (so cannot determine roundint and is.binary for the variables).</span></span>
-<span><span class="co">## To silence this warning:</span></span>
-<span><span class="co">##     Call prp with roundint=FALSE,</span></span>
-<span><span class="co">##     or rebuild the rpart model with model=TRUE.</span></span></code></pre>
-<p><img src="getting-started-w-naniar_files/figure-html/rpart-miss-1.png" width="500" style="display: block; margin: auto;"></p>
-<p>Here we can see that this produces quite a complex tree - this can be
-pruned back and the depth of the decision tree controlled.</p>
-</div>
-<div class="section level2">
-<h2 id="summary">Summary<a class="anchor" aria-label="anchor" href="#summary"></a>
-</h2>
-<p>The tools in <code>naniar</code> help us identify where missingness
-is, while maintaining a tidy workflow. We care about these mechanisms or
-these patterns because they can help us understand potential mechanisms,
-such as equipment failures, and then identify possible solutions based
-upon this evidence.</p>
-</div>
-<div class="section level2">
-<h2 id="future-development">Future development<a class="anchor" aria-label="anchor" href="#future-development"></a>
-</h2>
-<ul>
-<li>Make <code>naniar</code> work with big data tools like
-<code>sparklyr</code>, and <code>sparklingwater</code>.</li>
-<li>Further develop methods for handling and visualising imputations,
-and multiple imputation. Other plans to extend the
-<code>geom_miss_</code> family to include:</li>
-<li>Categorical variables</li>
-<li>Bivariate plots: scatterplots, density overlays</li>
-<li>Provide tools for assessing goodness of fit for classical approaches
-of MCAR, MAR, and MNAR (graphical inference from <code>nullabor</code>
-package)</li>
-</ul>
-</div>
-<div class="section level2">
-<h2 id="thank-you">Thank you<a class="anchor" aria-label="anchor" href="#thank-you"></a>
-</h2>
-<p>Firstly, thanks to Di Cook for giving the initial inspiration for the
-package and laying down the rich theory and literature that the work in
-<code>naniar</code> is built upon. Naming credit (once again!) goes to
-Miles McBain. Among various other things, Miles also worked out how to
-overload the missing data and make it work as a geom. Thanks also to
-Colin Fay for helping me understand tidy evaluation and for features
-such as <code>replace_with_na</code>, <code>miss_*_cumsum</code>, and
-more.</p>
-</div>
-<div class="section level2">
-<h2 id="references">References<a class="anchor" aria-label="anchor" href="#references"></a>
-</h2>
-<ul>
-<li>MANET: <a href="http://www.rosuda.org/MANET/" class="external-link uri">http://www.rosuda.org/MANET/</a>
-</li>
-<li>ggobi: <a href="https://en.wikipedia.org/wiki/GGobi" class="external-link uri">https://en.wikipedia.org/wiki/GGobi</a>
-</li>
-<li>visdat: <a href="https://github.com/ropensci/visdat" class="external-link uri">https://github.com/ropensci/visdat</a>
-</li>
-<li>Tierney NJ, Harden FA, Harden MJ, Mengersen, KA, Using decision
-trees to understand structure in missing data BMJ Open 2015;5:e007450.
-doi: 10.1136/bmjopen-2014-007450</li>
-</ul>
-</div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside>
-</div>
-
-
-
-    <footer><div class="pkgdown-footer-left">
-  <p></p>
-<p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
-</div>
-
-<div class="pkgdown-footer-right">
-  <p></p>
-<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
-</div>
-
-    </footer>
-</div>
-
-  
-
-  
-
-  </body>
-</html>
diff --git a/docs/articles/getting-started-w-naniar_files/figure-html/example-geom-point-1.png b/docs/articles/getting-started-w-naniar_files/figure-html/example-geom-point-1.png
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-      <h1>Getting Started with Narnia</h1>
-                        <h4 class="author">Nicholas Tierney</h4>
-
-            <h4 class="date">2017-07-25</h4>
-          </div>
-
-
-
-<div class="contents">
-<div id="introduction" class="section level1">
-<h1 class="hasAnchor">
-<a href="#introduction" class="anchor"></a>Introduction</h1>
-<p>Missing values are ubiquitous in data and need to be carefully explored and handled in the initial stages of analysis. In this vignette we describe the tools in the package <code>narnia</code> for exploring missing data structures with minimal deviation from the common workflows of ggplot and tidy data <span class="citation">[@Wickham2014; @Wickham2009]</span>.</p>
-<p>Sometimes researchers or analysts will introduce or describe a mechanism for missingness. For example, they might explain that data from a weather station might has a malfunction when there are extreme weather events, and does not record temperature data when gusts speeds are high. This seems like a nice simple, logical explanation. However, like all good explanations, this one is simple, but the process to get there, probably was not, and likely involved more time than you would have liked developing exploratory data analyses and models.</p>
-<p>So when someone presents a really obvious plot like this, with a nice sensible explanation, the initial thought might be:</p>
-<blockquote>
-<p>They worked it out themselves so quickly, so easy!</p>
-</blockquote>
-<p>As if they somehow <em>accidentally</em> solved the problem, it was so easy. They couldn’t not solve it. However, I think that if you manage to get that on the first go, that is more like turning around and throwing a rock into a lake and it landing in a cup in a boat. Unlikely.</p>
-<p>With that thought in mind, this vignette aims to work with the following three questions, using the tools developed in narnia and another package, visdat. Namely, how do we:</p>
-<ol style="list-style-type: decimal">
-<li>Start looking at missing data?</li>
-<li>Explore missingness mechanisms?</li>
-<li>Model missingness?</li>
-</ol>
-</div>
-<div id="how-do-we-start-looking-at-missing-data" class="section level1">
-<h1 class="hasAnchor">
-<a href="#how-do-we-start-looking-at-missing-data" class="anchor"></a>How do we start looking at missing data?</h1>
-<p>When you start with a dataset, you might do something where you look at the general summary, using functions such as:</p>
-<ul>
-<li><code>summary()</code></li>
-<li><code>str()</code></li>
-<li>
-<a href="https://github.com/ropenscilabs/skimr"><code><a href="http://www.rdocumentation.org/packages/skimr/topics/skim">skimr::skim</a></code></a>, or</li>
-<li><code><a href="http://dplyr.tidyverse.org/reference/reexports.html">dplyr::glimpse()</a></code></li>
-</ul>
-<p>These works really well when you’ve got a small amount of data, but when you have more data, you are generally limited by how much you can read.</p>
-<p>So before you start looking at missing data, you’ll need to look at the data, but what does that even mean?</p>
-<p>The package <code>visdat</code> helps you get a handle on this. <code>visdat</code> provides a visualisation of an entire data frame at once, and was heavily inspired by <a href="http://setosa.io/blog/2014/08/03/csv-fingerprints/"><code>csv-fingerprint</code></a>, and the missingness map functions from packages like <code><a href="http://www.rdocumentation.org/packages/Amelia/topics/missmap">Amelia::missmap</a></code>.</p>
-<p>There are two main functions in the <code>visdat</code> package:</p>
-<ul>
-<li>
-<code>vis_dat</code>, and</li>
-<li><code>vis_miss</code></li>
-</ul>
-<div id="vis_dat" class="section level2">
-<h2 class="hasAnchor">
-<a href="#vis_dat" class="anchor"></a><code>vis_dat</code>
-</h2>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">library</span>(visdat)
-<span class="kw"><a href="http://www.rdocumentation.org/packages/visdat/topics/vis_dat">vis_dat</a></span>(airquality)</code></pre></div>
-<p><img src="getting-started-w-narnia_files/figure-html/vis-dat-1.png" width="480" style="display: block; margin: auto;"></p>
-<p>These visualise the whole dataframe at once, and provide some useful information about whether the data is missing or not. It also provides information about the class of the data input into R.</p>
-<p>The function <code>vis_miss</code> provides a summary of whether the data is all present, and also provides small summaries in each column as to the amount of missings in each of the columns.</p>
-<div id="vis_miss" class="section level3">
-<h3 class="hasAnchor">
-<a href="#vis_miss" class="anchor"></a><code>vis_miss</code>
-</h3>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="http://www.rdocumentation.org/packages/visdat/topics/vis_miss">vis_miss</a></span>(airquality)</code></pre></div>
-<p><img src="getting-started-w-narnia_files/figure-html/vis-miss-cluster-vanilla-1.png" width="480" style="display: block; margin: auto;"></p>
-<p>To read more about the functions available in <code>visdat</code> see the vignette <a href="http://www.njtierney.com/visdat/articles/using_visdat.html">“Using visdat”</a></p>
-</div>
-</div>
-</div>
-<div id="exploring-missingness-relationships" class="section level1">
-<h1 class="hasAnchor">
-<a href="#exploring-missingness-relationships" class="anchor"></a>Exploring missingness relationships</h1>
-<p>We can identify key variables that are missing</p>
-<p>For further exploration, we need to explore the relationship amongst the variables in this data:</p>
-<ul>
-<li>Ozone,</li>
-<li>Solar.R</li>
-<li>Wind</li>
-<li>Temp</li>
-<li>Month</li>
-<li>Day</li>
-</ul>
-<p>This process of visualising the data as a heatmap allows you identify what is missing and where. For here though, are interested in exploring these missingness relationships.</p>
-<p>Typically, when exploring this data, you might want to explore the variables Solar.R and Ozone, and do something like this:</p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">library</span>(ggplot2)
-<span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/ggplot">ggplot</a></span>(airquality,
-       <span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/aes">aes</a></span>(<span class="dt">x =</span> Solar.R,
-           <span class="dt">y =</span> Ozone)) <span class="op">+</span><span class="st"> </span>
-<span class="st">  </span><span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/geom_point">geom_point</a></span>()</code></pre></div>
-<pre><code>## Warning: Removed 42 rows containing missing values (geom_point).</code></pre>
-<p><img src="getting-started-w-narnia_files/figure-html/unnamed-chunk-1-1.png" width="480" style="display: block; margin: auto;"></p>
-<p>The problem with this is that ggplot does not handle missings be default, and removes the missing values. This makes them hard to explore.</p>
-<p>Visualising missing data might sound a little strange - how do you visualise something that is not there? One approach to visualising missing data comes from ggobi and manet, where we replace “NA” values with values 10% lower than the minimum value in that variable. This is provided with the <code><a href="../reference/geom_miss_point.html">geom_miss_point()</a></code> ggplot2 geom, which we can illustrate by exploring the relationship between Ozone and Solar radiation from the airquality dataset.</p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/ggplot">ggplot</a></span>(airquality,
-       <span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/aes">aes</a></span>(<span class="dt">x =</span> Solar.R,
-           <span class="dt">y =</span> Ozone)) <span class="op">+</span><span class="st"> </span>
-<span class="st">  </span><span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/geom_point">geom_point</a></span>()</code></pre></div>
-<pre><code>## Warning: Removed 42 rows containing missing values (geom_point).</code></pre>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">library</span>(narnia)
-
-<span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/ggplot">ggplot</a></span>(airquality,
-       <span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/aes">aes</a></span>(<span class="dt">x =</span> Solar.R,
-           <span class="dt">y =</span> Ozone)) <span class="op">+</span><span class="st"> </span>
-<span class="st">  </span><span class="kw"><a href="../reference/geom_miss_point.html">geom_miss_point</a></span>()</code></pre></div>
-<p><img src="getting-started-w-narnia_files/figure-html/unnamed-chunk-2-1.png" width="50%" style="display: block; margin: auto;"><img src="getting-started-w-narnia_files/figure-html/unnamed-chunk-2-2.png" width="50%" style="display: block; margin: auto;"></p>
-<p><strong>Facets!</strong></p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/ggplot">ggplot</a></span>(airquality,
-       <span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/aes">aes</a></span>(<span class="dt">x =</span> Solar.R,
-           <span class="dt">y =</span> Ozone)) <span class="op">+</span><span class="st"> </span>
-<span class="st">  </span><span class="kw"><a href="../reference/geom_miss_point.html">geom_miss_point</a></span>() <span class="op">+</span><span class="st"> </span>
-<span class="st">  </span><span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/facet_wrap">facet_wrap</a></span>(<span class="op">~</span>Month)</code></pre></div>
-<p><img src="getting-started-w-narnia_files/figure-html/ggmissing-facet-1.png" width="70%" style="display: block; margin: auto;"></p>
-<p><strong>Themes!</strong></p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/ggplot">ggplot</a></span>(airquality,
-       <span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/aes">aes</a></span>(<span class="dt">x =</span> Solar.R,
-           <span class="dt">y =</span> Ozone)) <span class="op">+</span><span class="st"> </span>
-<span class="st">  </span><span class="kw"><a href="../reference/geom_miss_point.html">geom_miss_point</a></span>() <span class="op">+</span><span class="st"> </span>
-<span class="st">  </span><span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/facet_wrap">facet_wrap</a></span>(<span class="op">~</span>Month) <span class="op">+</span><span class="st"> </span>
-<span class="st">  </span><span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/ggtheme">theme_dark</a></span>()</code></pre></div>
-<p><img src="getting-started-w-narnia_files/figure-html/ggmissing-theme-1.png" width="70%" style="display: block; margin: auto;"></p>
-<div id="visualising-missings-in-variables" class="section level2">
-<h2 class="hasAnchor">
-<a href="#visualising-missings-in-variables" class="anchor"></a>Visualising missings in variables</h2>
-<p>Another approach to visualising the missings in a dataset is to use the <code>gg_miss_var</code> plot:</p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="../reference/gg_miss_var.html">gg_miss_var</a></span>(airquality)</code></pre></div>
-<p><img src="getting-started-w-narnia_files/figure-html/unnamed-chunk-3-1.png" width="480" style="display: block; margin: auto;"></p>
-<p>This creates a <code>ggplot2</code> object with the number of missing values for each variable, ordered from most missing to least missing. Under the hood, this is powered using <code><a href="../reference/miss_var_summary.html">miss_var_summary()</a></code>, described later.</p>
-<p>The plots created with the <code>gg_miss</code> family all have a basic theme, but you can customise them, just like usual ggplot objects. If you call any ggplot customisation functions with a <code>gg_miss</code> object, the default args will be overridden.</p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="../reference/gg_miss_var.html">gg_miss_var</a></span>(airquality) <span class="op">+</span><span class="st"> </span><span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/ggtheme">theme_bw</a></span>() </code></pre></div>
-<p><img src="getting-started-w-narnia_files/figure-html/unnamed-chunk-4-1.png" width="480" style="display: block; margin: auto;"></p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="../reference/gg_miss_var.html">gg_miss_var</a></span>(airquality) <span class="op">+</span><span class="st"> </span><span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/labs">labs</a></span>(<span class="dt">y =</span> <span class="st">"Look at all the missing ones"</span>)</code></pre></div>
-<p><img src="getting-started-w-narnia_files/figure-html/unnamed-chunk-4-2.png" width="480" style="display: block; margin: auto;"></p>
-</div>
-</div>
-<div id="shadow-matrix-a-tidy-way-of-representing-missing-values" class="section level1">
-<h1 class="hasAnchor">
-<a href="#shadow-matrix-a-tidy-way-of-representing-missing-values" class="anchor"></a>shadow matrix: A tidy way of representing missing values</h1>
-<p>Representing missing data structure is achieved using the shadow matrix, introduced in <a href="https://www.researchgate.net/publication/2758672_Missing_Data_in_Interactive_High-Dimensional_Data_Visualization">Swayne and Buja</a>. The shadow matrix is the same dimension as the data, and consists of binary indicators of missingness of data values, where missing is represented as “NA”, and not missing is represented as “!NA”. Although these may be represented as 1 and 0, respectively. This representation can be seen in the figure below, adding the suffix “_NA" to the variables. This structure can also be extended to allow for additional factor levels to be created. For example 0 indicates data presence, 1 indicates missing values, 2 indicates imputed value, and 3 might indicate a particular type or class of missingness, where reasons for missingness might be known or inferred. The data matrix can also be augmented to include the shadow matrix, which facilitates visualisation of univariate and bivariate missing data visualisations. Another format is to display it in long form, which facilitates heatmap style visualisations. This approach can be very helpful for giving an overview of which variables contain the most missingness. Methods can also be applied to rearrange rows and columns to find clusters, and identify other interesting features of the data that may have previously been hidden or unclear.</p>
-<p><img src="missingness-data-structures.png" width="800px" style="display: block; margin: auto;"></p>
-<p><strong>Illustration of data structures for facilitating visualisation of missings and not missings</strong></p>
-<p>The <code>shadow</code> functions provide a way to keep track of missing values. The <code>as_shadow</code> function creates a dataframe with the same set of columns, but with the column names added a suffix <code>_NA</code></p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="../reference/as_shadow.html">as_shadow</a></span>(airquality)</code></pre></div>
-<pre><code>## # A tibble: 153 x 6
-##    Ozone_NA Solar.R_NA Wind_NA Temp_NA Month_NA Day_NA
-##      &lt;fctr&gt;     &lt;fctr&gt;  &lt;fctr&gt;  &lt;fctr&gt;   &lt;fctr&gt; &lt;fctr&gt;
-##  1      !NA        !NA     !NA     !NA      !NA    !NA
-##  2      !NA        !NA     !NA     !NA      !NA    !NA
-##  3      !NA        !NA     !NA     !NA      !NA    !NA
-##  4      !NA        !NA     !NA     !NA      !NA    !NA
-##  5       NA         NA     !NA     !NA      !NA    !NA
-##  6      !NA         NA     !NA     !NA      !NA    !NA
-##  7      !NA        !NA     !NA     !NA      !NA    !NA
-##  8      !NA        !NA     !NA     !NA      !NA    !NA
-##  9      !NA        !NA     !NA     !NA      !NA    !NA
-## 10       NA        !NA     !NA     !NA      !NA    !NA
-## # ... with 143 more rows</code></pre>
-<p>The <code>bind_shadow</code> argument attaches a shadow to the current dataframe</p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">aq_shadow &lt;-<span class="st"> </span><span class="kw"><a href="../reference/bind_shadow.html">bind_shadow</a></span>(airquality)
-
-<span class="kw">library</span>(dplyr)</code></pre></div>
-<pre><code>##
-## Attaching package: 'dplyr'</code></pre>
-<pre><code>## The following objects are masked from 'package:stats':
-##
-##     filter, lag</code></pre>
-<pre><code>## The following objects are masked from 'package:base':
-##
-##     intersect, setdiff, setequal, union</code></pre>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="http://dplyr.tidyverse.org/reference/reexports.html">glimpse</a></span>(aq_shadow)</code></pre></div>
-<pre><code>## Observations: 153
-## Variables: 12
-## $ Ozone      &lt;int&gt; 41, 36, 12, 18, NA, 28, 23, 19, 8, NA, 7, 16, 11, 1...
-## $ Solar.R    &lt;int&gt; 190, 118, 149, 313, NA, NA, 299, 99, 19, 194, NA, 2...
-## $ Wind       &lt;dbl&gt; 7.4, 8.0, 12.6, 11.5, 14.3, 14.9, 8.6, 13.8, 20.1, ...
-## $ Temp       &lt;int&gt; 67, 72, 74, 62, 56, 66, 65, 59, 61, 69, 74, 69, 66,...
-## $ Month      &lt;int&gt; 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, ...
-## $ Day        &lt;int&gt; 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, ...
-## $ Ozone_NA   &lt;fctr&gt; !NA, !NA, !NA, !NA, NA, !NA, !NA, !NA, !NA, NA, !N...
-## $ Solar.R_NA &lt;fctr&gt; !NA, !NA, !NA, !NA, NA, NA, !NA, !NA, !NA, !NA, NA...
-## $ Wind_NA    &lt;fctr&gt; !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, ...
-## $ Temp_NA    &lt;fctr&gt; !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, ...
-## $ Month_NA   &lt;fctr&gt; !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, ...
-## $ Day_NA     &lt;fctr&gt; !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, !NA, ...</code></pre>
-<p>Doing this provides a consistent syntax for referring to variables with missing values.</p>
-<p><code><a href="../reference/bind_shadow.html">bind_shadow()</a></code> also provides a useful pattern to explore missing values by grouping by the missing/complete of one variable and looking at the mean and other summary values. Below we show the mean, sd, variance, and min and max values of Solar.R for when Ozone is present, and when it is missing.</p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">airquality <span class="op">%&gt;%</span>
-<span class="st">  </span><span class="kw"><a href="../reference/bind_shadow.html">bind_shadow</a></span>() <span class="op">%&gt;%</span>
-<span class="st">  </span><span class="kw"><a href="http://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(Ozone_NA) <span class="op">%&gt;%</span>
-<span class="st">  </span><span class="kw"><a href="http://dplyr.tidyverse.org/reference/summarise_all.html">summarise_at</a></span>(<span class="dt">.vars =</span> <span class="st">"Solar.R"</span>,
-               <span class="dt">.funs =</span> <span class="kw">c</span>(<span class="st">"mean"</span>, <span class="st">"sd"</span>, <span class="st">"var"</span>, <span class="st">"min"</span>, <span class="st">"max"</span>),
-               <span class="dt">na.rm =</span> <span class="ot">TRUE</span>)</code></pre></div>
-<pre><code>## # A tibble: 2 x 6
-##   Ozone_NA     mean       sd      var   min   max
-##     &lt;fctr&gt;    &lt;dbl&gt;    &lt;dbl&gt;    &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt;
-## 1      !NA 184.8018 91.15230 8308.742     7   334
-## 2       NA 189.5143 87.69478 7690.375    31   332</code></pre>
-<p>Below, we can plot the distribution of Temperature, plotting for values of temperature when Ozone is missing, and when it is not missing.</p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/ggplot">ggplot</a></span>(aq_shadow,
-       <span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/aes">aes</a></span>(<span class="dt">x =</span> Temp,
-           <span class="dt">colour =</span> Ozone_NA)) <span class="op">+</span><span class="st"> </span>
-<span class="st">  </span><span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/geom_density">geom_density</a></span>()</code></pre></div>
-<p><img src="getting-started-w-narnia_files/figure-html/shadow-plot-1.png" width="60%" style="display: block; margin: auto;"></p>
-<p>Binding the shadow here also has great benefits when combined with imputation.</p>
-</div>
-<div id="visualising-imputed-values" class="section level1">
-<h1 class="hasAnchor">
-<a href="#visualising-imputed-values" class="anchor"></a>Visualising imputed values</h1>
-<p>Using the easy-to-use <code>simputation</code> package, we impute values for Ozone, then visualise the data:</p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">library</span>(simputation)
-<span class="kw">library</span>(dplyr)
-
-airquality <span class="op">%&gt;%</span>
-<span class="st">  </span><span class="kw"><a href="http://www.rdocumentation.org/packages/simputation/topics/impute_lm">impute_lm</a></span>(Ozone <span class="op">~</span><span class="st"> </span>Temp <span class="op">+</span><span class="st"> </span>Wind) <span class="op">%&gt;%</span>
-<span class="st">  </span><span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/ggplot">ggplot</a></span>(<span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/aes">aes</a></span>(<span class="dt">x =</span> Temp,
-             <span class="dt">y =</span> Ozone)) <span class="op">+</span><span class="st"> </span>
-<span class="st">  </span><span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/geom_point">geom_point</a></span>()</code></pre></div>
-<p><img src="getting-started-w-narnia_files/figure-html/unnamed-chunk-8-1.png" width="480" style="display: block; margin: auto;"></p>
-<p>Note that we no longer get any errors regarding missing observations - because they are all imputed! But this comes at a cost: we also no longer have information about where the imputations are - they are now sort of invisible.</p>
-<p>Using the shadow matrix to keep track of where the missings are, you can actually keep track of the imputations, by colouring by what was previously missing in Ozone.</p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">aq_shadow <span class="op">%&gt;%</span>
-<span class="st">  </span><span class="kw"><a href="http://www.rdocumentation.org/packages/simputation/topics/impute_lm">impute_lm</a></span>(Ozone <span class="op">~</span><span class="st"> </span>Temp <span class="op">+</span><span class="st"> </span>Wind) <span class="op">%&gt;%</span>
-<span class="st">  </span><span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/ggplot">ggplot</a></span>(<span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/aes">aes</a></span>(<span class="dt">x =</span> Temp,
-             <span class="dt">y =</span> Ozone,
-             <span class="dt">colour =</span> Ozone_NA)) <span class="op">+</span><span class="st"> </span>
-<span class="st">  </span><span class="kw"><a href="http://www.rdocumentation.org/packages/ggplot2/topics/geom_point">geom_point</a></span>()</code></pre></div>
-<p><img src="getting-started-w-narnia_files/figure-html/unnamed-chunk-9-1.png" width="480" style="display: block; margin: auto;"></p>
-<div id="numerical-summaries-of-missing-values" class="section level2">
-<h2 class="hasAnchor">
-<a href="#numerical-summaries-of-missing-values" class="anchor"></a>Numerical summaries of missing values</h2>
-<p><code>narnia</code> also provide numerical summaries for missing data. Two convenient counters of complete values and missings are <code>n_miss</code> and <code>n_complete</code>. These work on both dataframes and vectors, similar to <code><a href="http://dplyr.tidyverse.org/reference/n_distinct.html">dplyr::n_distinct</a></code></p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">dplyr<span class="op">::</span><span class="kw"><a href="http://dplyr.tidyverse.org/reference/n_distinct.html">n_distinct</a></span>(airquality)</code></pre></div>
-<pre><code>## [1] 153</code></pre>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">dplyr<span class="op">::</span><span class="kw"><a href="http://dplyr.tidyverse.org/reference/n_distinct.html">n_distinct</a></span>(airquality<span class="op">$</span>Ozone)</code></pre></div>
-<pre><code>## [1] 68</code></pre>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="../reference/n_miss.html">n_miss</a></span>(airquality)</code></pre></div>
-<pre><code>## [1] 44</code></pre>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="../reference/n_miss.html">n_miss</a></span>(airquality<span class="op">$</span>Ozone)</code></pre></div>
-<pre><code>## [1] 37</code></pre>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="../reference/n_complete.html">n_complete</a></span>(airquality)</code></pre></div>
-<pre><code>## [1] 874</code></pre>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="../reference/n_complete.html">n_complete</a></span>(airquality<span class="op">$</span>Ozone)</code></pre></div>
-<pre><code>## [1] 116</code></pre>
-<p>The syntax for the other numerical sumamries in <code>narnia</code> are <code>miss_</code>, and then <code>case</code>, <code>var</code>, or <code>df</code>, and then <code>summary</code> or <code>table</code>. There are also some summary functions for <code>ts</code> objects that are being worked on, which currently have <code>miss_ts_run</code> and <code>miss_ts_summary</code> functions.</p>
-<p>To demonstrate, below are the <code>miss_case_*</code> family of functions.</p>
-<p><code>miss_case_pct</code> returns a numeric value describing the percent of missing values in the dataframe.</p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="../reference/miss_case_pct.html">miss_case_pct</a></span>(airquality)</code></pre></div>
-<pre><code>## [1] 27.45098</code></pre>
-<p><code>miss_case_summary</code> returns a numeric value that describes the number of missings in a given case (aka row), the percent of missings in that row.</p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="../reference/miss_case_summary.html">miss_case_summary</a></span>(airquality)</code></pre></div>
-<pre><code>## # A tibble: 153 x 3
-##     case n_miss  pct_miss
-##    &lt;int&gt;     &lt;int&gt;    &lt;dbl&gt;
-##  1     1         0  0.00000
-##  2     2         0  0.00000
-##  3     3         0  0.00000
-##  4     4         0  0.00000
-##  5     5         2 33.33333
-##  6     6         1 16.66667
-##  7     7         0  0.00000
-##  8     8         0  0.00000
-##  9     9         0  0.00000
-## 10    10         1 16.66667
-## # ... with 143 more rows</code></pre>
-<p><code>miss_case_table</code> tabulates the number of missing values in a case / row. Below, this shows the number of missings in a case:</p>
-<ul>
-<li>There are 111 cases with 0 missings, which comprises about 72% of the data.</li>
-<li>There are then 40 cases with 1 missing, these make up 26% of the data.</li>
-<li>There are then 2 cases with 2 missing - these make up 1% of the data.</li>
-</ul>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="../reference/miss_case_table.html">miss_case_table</a></span>(airquality)</code></pre></div>
-<pre><code>## # A tibble: 3 x 3
-##   n_miss_in_case n_cases  pct_miss
-##               &lt;int&gt;   &lt;int&gt;    &lt;dbl&gt;
-## 1                 0     111 72.54902
-## 2                 1      40 26.14379
-## 3                 2       2  1.30719</code></pre>
-<p>There are then the <code>miss_var_*</code> family of functions.</p>
-<p>Similar to <code>miss_case_pct</code>, <code>miss_var_pct</code> returns the percent of variables that contain a missing value.</p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="../reference/miss_var_pct.html">miss_var_pct</a></span>(airquality)</code></pre></div>
-<pre><code>## [1] 33.33333</code></pre>
-<p><code>miss_var_summary</code> then returns the number of missing values in a variable, and the percent missing in that variable.</p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="../reference/miss_var_summary.html">miss_var_summary</a></span>(airquality)</code></pre></div>
-<pre><code>## # A tibble: 6 x 3
-##   variable n_miss   pct_miss
-##      &lt;chr&gt;     &lt;int&gt;     &lt;dbl&gt;
-## 1    Ozone        37 24.183007
-## 2  Solar.R         7  4.575163
-## 3     Wind         0  0.000000
-## 4     Temp         0  0.000000
-## 5    Month         0  0.000000
-## 6      Day         0  0.000000</code></pre>
-<p>Finally, <code>miss_var_table</code>. This describes the number of missings in a variable.</p>
-<ul>
-<li>There are 4 variables with 0 missings, comprising 66.67% of variables in the dataset.</li>
-<li>There is 1 variable with 7 missings</li>
-<li>There is 1 variable with 37 missings</li>
-</ul>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="../reference/miss_var_table.html">miss_var_table</a></span>(airquality)</code></pre></div>
-<pre><code>## # A tibble: 3 x 3
-##   n_miss_in_var n_vars  pct_miss
-##              &lt;int&gt;  &lt;int&gt;    &lt;dbl&gt;
-## 1                0      4 66.66667
-## 2                7      1 16.66667
-## 3               37      1 16.66667</code></pre>
-<p>There are also summary functions for exploring missings that occur over a particular span or period of the dataset, or the number of missings in a single run:</p>
-<ul>
-<li>
-<code><a href="../reference/miss_var_run.html">miss_var_run()</a></code>, and</li>
-<li><code><a href="../reference/miss_var_span.html">miss_var_span()</a></code></li>
-</ul>
-<p><code>miss_var_run</code> can be particularly useful in time series data, as it allows you to provide summaries for the number of missings or complete values in a single run. The function <code><a href="../reference/miss_var_run.html">miss_var_run()</a></code> provides a data.frame of the run length of missings and complete values. To explore this function we will use the built-in dataset, <code>pedestrian</code>, which contains hourly counts of pedestrians from four locations around Melbourne, Australia, from 2016.</p>
-<p>To use <code>miss_var_run</code>, you specify the variable that you want to explore the runs of missingness for, in this case, <code>hourly_counts</code>:</p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="../reference/miss_var_run.html">miss_var_run</a></span>(pedestrian,
-             hourly_counts)</code></pre></div>
-<pre><code>## # A tibble: 35 x 2
-##    run_length    is_na
-##         &lt;int&gt;    &lt;chr&gt;
-##  1       6628 complete
-##  2          1  missing
-##  3       5250 complete
-##  4        624  missing
-##  5       3652 complete
-##  6          1  missing
-##  7       1290 complete
-##  8        744  missing
-##  9       7420 complete
-## 10          1  missing
-## # ... with 25 more rows</code></pre>
-<p><code><a href="../reference/miss_var_span.html">miss_var_span()</a></code> is used to determine the number of missings over a specified repeating span of rows in variable of a dataframe. Similar to <code>miss_var_run</code>, you specify the variable that you wish to explore, you then also specify the size of the span with the <code>span_every</code> argument.</p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="../reference/miss_var_span.html">miss_var_span</a></span>(pedestrian,
-              hourly_counts,
-              <span class="dt">span_every =</span> <span class="dv">100</span>)</code></pre></div>
-<pre><code>## # A tibble: 377 x 5
-##    span_counter n_miss n_complete prop_miss prop_complete
-##           &lt;int&gt;  &lt;int&gt;      &lt;dbl&gt;     &lt;dbl&gt;         &lt;dbl&gt;
-##  1            1      0        100         0             1
-##  2            2      0        100         0             1
-##  3            3      0        100         0             1
-##  4            4      0        100         0             1
-##  5            5      0        100         0             1
-##  6            6      0        100         0             1
-##  7            7      0        100         0             1
-##  8            8      0        100         0             1
-##  9            9      0        100         0             1
-## 10           10      0        100         0             1
-## # ... with 367 more rows</code></pre>
-<p>The final question we proposed in this vignette was:</p>
-<ol start="3" style="list-style-type: decimal">
-<li>Can we model missingness?</li>
-</ol>
-<p>Sometimes it can be impractical to explore all of the variables that have missing data. One approach, however, is to model missing data using methods from Tierney et el. (2015).</p>
-<p>Here, the approach is to predict the proportion of missingness in a given case, using all variables. There is a little helper function to add a column with the proportion of cases or rows missing - <code>add_prop_miss</code>. This created a column named “prop_miss”, which is the proportion of missing values in that row.</p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">airquality <span class="op">%&gt;%</span>
-<span class="st">  </span><span class="kw"><a href="../reference/add_prop_miss.html">add_prop_miss</a></span>() <span class="op">%&gt;%</span>
-<span class="st">  </span><span class="kw">head</span>()</code></pre></div>
-<pre><code>## # A tibble: 6 x 7
-##   Ozone Solar.R  Wind  Temp Month   Day prop_miss_all
-##   &lt;int&gt;   &lt;int&gt; &lt;dbl&gt; &lt;int&gt; &lt;int&gt; &lt;int&gt;         &lt;dbl&gt;
-## 1    41     190   7.4    67     5     1     0.0000000
-## 2    36     118   8.0    72     5     2     0.0000000
-## 3    12     149  12.6    74     5     3     0.0000000
-## 4    18     313  11.5    62     5     4     0.0000000
-## 5    NA      NA  14.3    56     5     5     0.3333333
-## 6    28      NA  14.9    66     5     6     0.1666667</code></pre>
-<p>We can then use a model like decision trees to predict which variables and their values are important for predicting the proportion of missingness:</p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">library</span>(rpart)
-<span class="kw">library</span>(rpart.plot)
-
-airquality <span class="op">%&gt;%</span>
-<span class="st">  </span><span class="kw"><a href="../reference/add_prop_miss.html">add_prop_miss</a></span>() <span class="op">%&gt;%</span>
-<span class="st">  </span><span class="kw"><a href="http://www.rdocumentation.org/packages/rpart/topics/rpart">rpart</a></span>(prop_miss_all <span class="op">~</span><span class="st"> </span>., <span class="dt">data =</span> .) <span class="op">%&gt;%</span>
-<span class="st">  </span><span class="kw"><a href="http://www.rdocumentation.org/packages/rpart.plot/topics/prp">prp</a></span>(<span class="dt">type =</span> <span class="dv">4</span>, <span class="dt">extra =</span> <span class="dv">101</span>, <span class="dt">prefix =</span> <span class="st">"Prop. Miss = "</span>)</code></pre></div>
-<p><img src="getting-started-w-narnia_files/figure-html/rpart-miss-1.png" width="480" style="display: block; margin: auto;"></p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="co"># library(visdat)</span>
-<span class="co"># vis_miss(messy_airquality)</span></code></pre></div>
-<p>Here we can see that this produces quite a complex tree - this can be pruned back and the depth of the decision tree controlled.</p>
-</div>
-</div>
-<div id="summary" class="section level1">
-<h1 class="hasAnchor">
-<a href="#summary" class="anchor"></a>Summary</h1>
-<p>The tools in <code>narnia</code> help us identify where missingness is, while maintaining a tidy workflow. We care about these mechanisms or these patterns because they can help us understand potential mechanisms, such as equipment failures, and then identify possible solutions based upon this evidence.</p>
-</div>
-<div id="future-development" class="section level1">
-<h1 class="hasAnchor">
-<a href="#future-development" class="anchor"></a>Future development</h1>
-<ul>
-<li>Continue making <code>narnia</code> play well with <code>dplyr</code> and <code>tidyr</code>.</li>
-<li>Make <code>narnia</code> work with big data tools like <code>sparklyr</code>, and <code>sparklingwater</code>.</li>
-<li>Expand ggplot <code>geom_miss_*</code> family.</li>
-<li>Further develop methods for handling and visualising imputations, and multiple imputation.</li>
-</ul>
-</div>
-<div id="thank-you" class="section level1">
-<h1 class="hasAnchor">
-<a href="#thank-you" class="anchor"></a>Thank you</h1>
-<p>A huge thanks of course to Di Cook and Miles McBain for their assistance on this project, and its development. In particular, I thank Di for providing the large conceptual ideas of how to display missings, and the use of the shadow matrix. I also thank Miles for his instrumental work in getting <code>stat_missing_point</code> and <code><a href="../reference/geom_miss_point.html">geom_miss_point()</a></code> working as they do now.</p>
-</div>
-<div id="references" class="section level1">
-<h1 class="hasAnchor">
-<a href="#references" class="anchor"></a>References</h1>
-<ul>
-<li>MANET: <a href="http://www.rosuda.org/MANET/" class="uri">http://www.rosuda.org/MANET/</a>
-</li>
-<li>ggobi: <a href="http://www.ggobi.org/" class="uri">http://www.ggobi.org/</a>
-</li>
-<li>visdat: <a href="https://www.github.com/njtierney/visdat" class="uri">https://www.github.com/njtierney/visdat</a>
-</li>
-<li>Tierney NJ, Harden FA, Harden MJ, Mengersen, KA, Using decision trees to understand structure in missing data BMJ Open 2015;5:e007450. doi: 10.1136/bmjopen-2014-007450</li>
-</ul>
-</div>
-</div>
-  </div>
-
-  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
-        <div id="tocnav">
-      <h2 class="hasAnchor">
-<a href="#tocnav" class="anchor"></a>Contents</h2>
-      <ul class="nav nav-pills nav-stacked">
-<li><a href="#introduction">Introduction</a></li>
-      <li>
-<a href="#how-do-we-start-looking-at-missing-data">How do we start looking at missing data?</a><ul class="nav nav-pills nav-stacked">
-<li><a href="#vis_dat"><code>vis_dat</code></a></li>
-      </ul>
-</li>
-      <li>
-<a href="#exploring-missingness-relationships">Exploring missingness relationships</a><ul class="nav nav-pills nav-stacked">
-<li><a href="#visualising-missings-in-variables">Visualising missings in variables</a></li>
-      </ul>
-</li>
-      <li><a href="#shadow-matrix-a-tidy-way-of-representing-missing-values">shadow matrix: A tidy way of representing missing values</a></li>
-      <li>
-<a href="#visualising-imputed-values">Visualising imputed values</a><ul class="nav nav-pills nav-stacked">
-<li><a href="#numerical-summaries-of-missing-values">Numerical summaries of missing values</a></li>
-      </ul>
-</li>
-      <li><a href="#summary">Summary</a></li>
-      <li><a href="#future-development">Future development</a></li>
-      <li><a href="#thank-you">Thank you</a></li>
-      <li><a href="#references">References</a></li>
-      </ul>
-</div>
-      </div>
-
-</div>
-
-
-      <footer><div class="copyright">
-  <p>Developed by Nicholas Tierney, Di Cook, Miles McBain.</p>
-</div>
-
-<div class="pkgdown">
-  <p>Site built with <a href="http://hadley.github.io/pkgdown/">pkgdown</a>.</p>
-</div>
-
-      </footer>
-</div>
-
-  </body>
-</html>
diff --git a/docs/articles/getting-started-w-narnia_files/figure-html/ggmissing-facet-1.png b/docs/articles/getting-started-w-narnia_files/figure-html/ggmissing-facet-1.png
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diff --git a/docs/articles/missingness-data-structures.png b/docs/articles/missingness-data-structures.png
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-      <img src="../logo.png" class="logo" alt=""><h1>Gallery of Missing Data Visualisations</h1>
-                        <h4 data-toc-skip class="author">Nicholas
-Tierney</h4>
-            
-            <h4 data-toc-skip class="date">2023-05-01</h4>
-      
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/vignettes/naniar-visualisation.Rmd" class="external-link"><code>vignettes/naniar-visualisation.Rmd</code></a></small>
-      <div class="d-none name"><code>naniar-visualisation.Rmd</code></div>
-    </div>
-
-    
-    
-<p>There are a variety of different plots to explore missing data
-available in the naniar package. This vignette simply showcases all of
-the visualisations. If you would like to know more about the philosophy
-of the <code>naniar</code> package, you should read the vignette <a href="http://naniar.njtierney.com/articles/getting-started-w-naniar.html">Getting
-Started with naniar</a>.</p>
-<p>A key point to remember with the visualisation tools in
-<code>naniar</code> is that there is a way to get the data from the plot
-out from the visualisation.</p>
-<div class="section level2">
-<h2 id="getting-started">Getting started<a class="anchor" aria-label="anchor" href="#getting-started"></a>
-</h2>
-<p>One of the first plots that I recommend you start with when you are
-first exploring your missing data, is the <code><a href="https://docs.ropensci.org/visdat/reference/vis_miss.html" class="external-link">vis_miss()</a></code> plot,
-which is re-exported from <a href="https://github.com/ropensci/visdat" class="external-link"><code>visdat</code></a>.</p>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/njtierney/naniar" class="external-link">naniar</a></span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu"><a href="https://docs.ropensci.org/visdat/reference/vis_miss.html" class="external-link">vis_miss</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/vis-miss-1.png" width="500" style="display: block; margin: auto;"></p>
-<p>This plot provides a specific visualiation of the amount of missing
-data, showing in black the location of missing values, and also
-providing information on the overall percentage of missing values
-overall (in the legend), and in each variable.</p>
-<div class="section level3">
-<h3 id="exploring-patterns-with-upsetr">Exploring patterns with UpSetR<a class="anchor" aria-label="anchor" href="#exploring-patterns-with-upsetr"></a>
-</h3>
-<p>An upset plot from the <code>UpSetR</code> package can be used to
-visualise the patterns of missingness, or rather the combinations of
-missingness across cases. To see combinations of missingness and
-intersections of missingness amongst variables, use the
-<code>gg_miss_upset</code> function:</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/gg_miss_upset.html">gg_miss_upset</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/gg-miss-upset-1.png" width="500" style="display: block; margin: auto;"></p>
-<p>This tells us:</p>
-<ul>
-<li>Only Ozone and Solar.R have missing values</li>
-<li>Ozone has the most missing values</li>
-<li>There are 2 cases where both Solar.R and Ozone have missing values
-together</li>
-</ul>
-<p>We can explore this with more complex data, such as riskfactors:</p>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/gg_miss_upset.html">gg_miss_upset</a></span><span class="op">(</span><span class="va">riskfactors</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/upset-plot-riskfactors-1.png" width="500" style="display: block; margin: auto;"></p>
-<p>The default option of <code>gg_miss_upset</code> is taken from
-<code><a href="https://rdrr.io/pkg/UpSetR/man/upset.html" class="external-link">UpSetR::upset</a></code> - which is to use up to 5 sets and up to 40
-interactions. Here, setting <code>nsets = 5</code> means to look at 5
-variables and their combinations. The number of combinations or rather
-<code>intersections</code> is controlled by <code>nintersects</code>.
-You could, for example look at all of the number of missing variables
-using <code>n_var_miss</code>:</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="co"># how many missings?</span></span>
-<span><span class="fu"><a href="../reference/n-var-case-miss.html">n_var_miss</a></span><span class="op">(</span><span class="va">riskfactors</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## [1] 24</span></span></code></pre>
-<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/gg_miss_upset.html">gg_miss_upset</a></span><span class="op">(</span><span class="va">riskfactors</span>, nsets <span class="op">=</span> <span class="fu"><a href="../reference/n-var-case-miss.html">n_var_miss</a></span><span class="op">(</span><span class="va">riskfactors</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/gg-miss-upset-n-var-miss-1.png" width="500" style="display: block; margin: auto;"></p>
-<p>If there are 40 intersections, there will be up to 40 combinations of
-variables explored. The number of sets and intersections can be changed
-by passing arguments <code>nsets = 10</code> to look at 10 sets of
-variables, and <code>nintersects = 50</code> to look at 50
-intersections.</p>
-<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/gg_miss_upset.html">gg_miss_upset</a></span><span class="op">(</span><span class="va">riskfactors</span>, </span>
-<span>              nsets <span class="op">=</span> <span class="fl">10</span>,</span>
-<span>              nintersects <span class="op">=</span> <span class="fl">50</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/gg-miss-upset-n-sets-1.png" width="500" style="display: block; margin: auto;"></p>
-<p>Setting <code>nintersects</code> to <code>NA</code> it will plot all
-sets and all intersections.</p>
-<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/gg_miss_upset.html">gg_miss_upset</a></span><span class="op">(</span><span class="va">riskfactors</span>, </span>
-<span>              nsets <span class="op">=</span> <span class="fl">10</span>,</span>
-<span>              nintersects <span class="op">=</span> <span class="cn">NA</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/gg-miss-upset-nintersect-NA-1.png" width="500" style="display: block; margin: auto;"></p>
-</div>
-</div>
-<div class="section level2">
-<h2 id="exploring-missingness-mechanisms">Exploring Missingness Mechanisms<a class="anchor" aria-label="anchor" href="#exploring-missingness-mechanisms"></a>
-</h2>
-<p>There are a few different ways to explore different missing data
-mechanisms and relationships. One way incorporates the method of
-shifting missing values so that they can be visualised on the same axes
-as the regular values, and then colours the missing and not missing
-points. This is implemented with <code><a href="../reference/geom_miss_point.html">geom_miss_point()</a></code>.</p>
-<div class="section level3">
-<h3 id="geom_miss_point">
-<code>geom_miss_point</code><a class="anchor" aria-label="anchor" href="#geom_miss_point"></a>
-</h3>
-<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span>
-<span><span class="co"># using regular geom_point()</span></span>
-<span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">airquality</span>,</span>
-<span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Ozone</span>,</span>
-<span>           y <span class="op">=</span> <span class="va">Solar.R</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
-<span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_point.html" class="external-link">geom_point</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## Warning: Removed 42 rows containing missing values (`geom_point()`).</span></span></code></pre>
-<p><img src="naniar-visualisation_files/figure-html/ggplot-geom-miss-point-1.png" width="500" style="display: block; margin: auto;"></p>
-<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/njtierney/naniar" class="external-link">naniar</a></span><span class="op">)</span></span>
-<span></span>
-<span><span class="co"># using  geom_miss_point()</span></span>
-<span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">airquality</span>,</span>
-<span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Ozone</span>,</span>
-<span>           y <span class="op">=</span> <span class="va">Solar.R</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
-<span> <span class="fu"><a href="../reference/geom_miss_point.html">geom_miss_point</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/ggplot-geom-miss-point-2.png" width="500" style="display: block; margin: auto;"></p>
-<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="co"># Facets!</span></span>
-<span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">airquality</span>,</span>
-<span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Ozone</span>,</span>
-<span>           y <span class="op">=</span> <span class="va">Solar.R</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
-<span> <span class="fu"><a href="../reference/geom_miss_point.html">geom_miss_point</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span> </span>
-<span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/facet_wrap.html" class="external-link">facet_wrap</a></span><span class="op">(</span><span class="op">~</span><span class="va">Month</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/ggplot-geom-miss-point-3.png" width="500" style="display: block; margin: auto;"></p>
-<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="co"># Themes</span></span>
-<span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">airquality</span>,</span>
-<span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Ozone</span>,</span>
-<span>           y <span class="op">=</span> <span class="va">Solar.R</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
-<span> <span class="fu"><a href="../reference/geom_miss_point.html">geom_miss_point</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span> </span>
-<span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_dark</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/ggplot-geom-miss-point-4.png" width="500" style="display: block; margin: auto;"></p>
-</div>
-</div>
-<div class="section level2">
-<h2 id="general-visual-summaries-of-missing-data">General visual summaries of missing data<a class="anchor" aria-label="anchor" href="#general-visual-summaries-of-missing-data"></a>
-</h2>
-<p>Here are some function that provide quick summaries of missingness in
-your data, they all start with <code>gg_miss_</code> - so that they are
-easy to remember and tab-complete.</p>
-<div class="section level3">
-<h3 id="missingness-in-variables-with-gg_miss_var">Missingness in variables with <code>gg_miss_var</code><a class="anchor" aria-label="anchor" href="#missingness-in-variables-with-gg_miss_var"></a>
-</h3>
-<p>This plot shows the number of missing values in each variable in a
-dataset. It is powered by the <code><a href="../reference/miss_var_summary.html">miss_var_summary()</a></code>
-function.</p>
-<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/gg_miss_var.html">gg_miss_var</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/gg-miss-var-1.png" width="500" style="display: block; margin: auto;"></p>
-<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span>
-<span><span class="fu"><a href="../reference/gg_miss_var.html">gg_miss_var</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span> <span class="op">+</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span>y <span class="op">=</span> <span class="st">"Look at all the missing ones"</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/gg-miss-var-2.png" width="500" style="display: block; margin: auto;"></p>
-<p>If you wish, you can also change whether to show the % of missing
-instead with <code>show_pct = TRUE</code>.</p>
-<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/gg_miss_var.html">gg_miss_var</a></span><span class="op">(</span><span class="va">airquality</span>, show_pct <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/gg-miss-var-show-pct-1.png" width="500" style="display: block; margin: auto;"></p>
-<p>You can also plot the number of missings in a variable grouped by
-another variable using the <code>facet</code> argument.</p>
-<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/gg_miss_var.html">gg_miss_var</a></span><span class="op">(</span><span class="va">airquality</span>,</span>
-<span>            facet <span class="op">=</span> <span class="va">Month</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/gg-miss-var-group-1.png" width="500" style="display: block; margin: auto;"></p>
-</div>
-<div class="section level3">
-<h3 id="missingness-in-cases-with-gg_miss_case">Missingness in cases with <code>gg_miss_case</code><a class="anchor" aria-label="anchor" href="#missingness-in-cases-with-gg_miss_case"></a>
-</h3>
-<p>This plot shows the number of missing values in each case. It is
-powered by the <code><a href="../reference/miss_case_summary.html">miss_case_summary()</a></code> function.</p>
-<div class="sourceCode" id="cb18"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/gg_miss_case.html">gg_miss_case</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/gg-miss-case-1.png" width="500" style="display: block; margin: auto;"></p>
-<div class="sourceCode" id="cb19"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/gg_miss_case.html">gg_miss_case</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span> <span class="op">+</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span>x <span class="op">=</span> <span class="st">"Number of Cases"</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/gg-miss-case-2.png" width="500" style="display: block; margin: auto;"></p>
-<p>You can also order by the number of cases using
-<code>order_cases = TRUE</code></p>
-<div class="sourceCode" id="cb20"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/gg_miss_case.html">gg_miss_case</a></span><span class="op">(</span><span class="va">airquality</span>, order_cases <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/gg-miss-case-order-by-case-1.png" width="500" style="display: block; margin: auto;"></p>
-<p>You can also explore the missingness in cases over some variable
-using <code>facet = Month</code></p>
-<div class="sourceCode" id="cb21"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/gg_miss_case.html">gg_miss_case</a></span><span class="op">(</span><span class="va">airquality</span>, facet <span class="op">=</span> <span class="va">Month</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/gg-miss-case-group-1.png" width="500" style="display: block; margin: auto;"></p>
-</div>
-<div class="section level3">
-<h3 id="missingness-across-factors-with-gg_miss_fct">Missingness across factors with <code>gg_miss_fct</code><a class="anchor" aria-label="anchor" href="#missingness-across-factors-with-gg_miss_fct"></a>
-</h3>
-<p>This plot shows the number of missings in each column, broken down by
-a categorical variable from the dataset. It is powered by a
-<code><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">dplyr::group_by</a></code> statement followed by
-<code><a href="../reference/miss_var_summary.html">miss_var_summary()</a></code>.</p>
-<div class="sourceCode" id="cb22"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/gg_miss_fct.html">gg_miss_fct</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">riskfactors</span>, fct <span class="op">=</span> <span class="va">marital</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## Warning: There was 1 warning in `mutate()`.</span></span>
-<span><span class="co">## <span style="color: #00BBBB;">ℹ</span> In argument: `marital = (function (x) ...`.</span></span>
-<span><span class="co">## Caused by warning:</span></span>
-<span><span class="co">## <span style="color: #BBBB00;">!</span> `fct_explicit_na()` was deprecated in forcats 1.0.0.</span></span>
-<span><span class="co">## <span style="color: #00BBBB;">ℹ</span> Please use `fct_na_value_to_level()` instead.</span></span>
-<span><span class="co">## <span style="color: #00BBBB;">ℹ</span> The deprecated feature was likely used in the <span style="color: #0000BB;">naniar</span> package.</span></span>
-<span><span class="co">##   Please report the issue at <span style="color: #0000BB; font-style: italic;">&lt;https://github.com/njtierney/naniar/issues&gt;</span>.</span></span></code></pre>
-<p><img src="naniar-visualisation_files/figure-html/gg-miss-fct-1.png" width="500" style="display: block; margin: auto;"></p>
-<div class="sourceCode" id="cb24"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span>
-<span><span class="fu"><a href="../reference/gg_miss_fct.html">gg_miss_fct</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">riskfactors</span>, fct <span class="op">=</span> <span class="va">marital</span><span class="op">)</span> <span class="op">+</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span>title <span class="op">=</span> <span class="st">"NA in Risk Factors and Marital status"</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/gg-miss-fct-2.png" width="500" style="display: block; margin: auto;"></p>
-<div class="sourceCode" id="cb25"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="co"># using group_by</span></span>
-<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## </span></span>
-<span><span class="co">## Attaching package: 'dplyr'</span></span></code></pre>
-<pre><code><span><span class="co">## The following objects are masked from 'package:stats':</span></span>
-<span><span class="co">## </span></span>
-<span><span class="co">##     filter, lag</span></span></code></pre>
-<pre><code><span><span class="co">## The following objects are masked from 'package:base':</span></span>
-<span><span class="co">## </span></span>
-<span><span class="co">##     intersect, setdiff, setequal, union</span></span></code></pre>
-<div class="sourceCode" id="cb29"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">riskfactors</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">marital</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/miss_var_summary.html">miss_var_summary</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## <span style="color: #949494;"># A tibble: 231 × 4</span></span></span>
-<span><span class="co">## <span style="color: #949494;"># Groups:   marital [7]</span></span></span>
-<span><span class="co">##    marital variable      n_miss pct_miss</span></span>
-<span><span class="co">##    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>          <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 1</span> Married smoke_stop       120    91.6 </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 2</span> Married pregnant         117    89.3 </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 3</span> Married smoke_last        84    64.1 </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 4</span> Married smoke_days        73    55.7 </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 5</span> Married drink_average     68    51.9 </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 6</span> Married health_poor       67    51.1 </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 7</span> Married drink_days        67    51.1 </span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 8</span> Married weight_lbs         6     4.58</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 9</span> Married bmi                6     4.58</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">10</span> Married diet_fruit         4     3.05</span></span>
-<span><span class="co">## <span style="color: #949494;"># ℹ 221 more rows</span></span></span></code></pre>
-<p><code>gg_miss_fct</code> can also be used to explore missingness
-along time, like so:</p>
-<div class="sourceCode" id="cb31"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/gg_miss_fct.html">gg_miss_fct</a></span><span class="op">(</span><span class="va">oceanbuoys</span>, <span class="va">year</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/unnamed-chunk-1-1.png" width="500" style="display: block; margin: auto;"></p>
-<div class="sourceCode" id="cb32"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="co"># to load who data</span></span>
-<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://tidyr.tidyverse.org" class="external-link">tidyr</a></span><span class="op">)</span></span>
-<span><span class="fu"><a href="../reference/gg_miss_fct.html">gg_miss_fct</a></span><span class="op">(</span><span class="va">who</span>, <span class="va">year</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/unnamed-chunk-1-2.png" width="500" style="display: block; margin: auto;"></p>
-<p>(Thanks to <a href="https://github.com/mpaulacaldas" class="external-link">Maria Paula
-Caldas</a> for inspiration for this visualisation, <a href="https://github.com/njtierney/naniar/issues/254" class="external-link">discussed
-here</a>)</p>
-</div>
-<div class="section level3">
-<h3 id="missingness-along-a-repeating-span-with-gg_miss_span">Missingness along a repeating span with
-<code>gg_miss_span</code><a class="anchor" aria-label="anchor" href="#missingness-along-a-repeating-span-with-gg_miss_span"></a>
-</h3>
-<p>This plot shows the number of missings in a given span, or breaksize,
-for a single selected variable. In this case we look at the span of
-<code>hourly_counts</code> from the pedestrian dataset. It is powered by
-the <code>miss_var_span</code> function</p>
-<div class="sourceCode" id="cb33"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="co"># data method</span></span>
-<span></span>
-<span><span class="fu"><a href="../reference/miss_var_span.html">miss_var_span</a></span><span class="op">(</span><span class="va">pedestrian</span>, <span class="va">hourly_counts</span>, span_every <span class="op">=</span> <span class="fl">3000</span><span class="op">)</span></span></code></pre></div>
-<pre><code><span><span class="co">## <span style="color: #949494;"># A tibble: 13 × 6</span></span></span>
-<span><span class="co">##    span_counter n_miss n_complete prop_miss prop_complete n_in_span</span></span>
-<span><span class="co">##           <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 1</span>            1      0       <span style="text-decoration: underline;">3</span>000  0                1          <span style="text-decoration: underline;">3</span>000</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 2</span>            2      0       <span style="text-decoration: underline;">3</span>000  0                1          <span style="text-decoration: underline;">3</span>000</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 3</span>            3      1       <span style="text-decoration: underline;">2</span>999  0.000<span style="text-decoration: underline;">333</span>         1.00       <span style="text-decoration: underline;">3</span>000</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 4</span>            4    121       <span style="text-decoration: underline;">2</span>879  0.040<span style="text-decoration: underline;">3</span>           0.960      <span style="text-decoration: underline;">3</span>000</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 5</span>            5    503       <span style="text-decoration: underline;">2</span>497  0.168            0.832      <span style="text-decoration: underline;">3</span>000</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 6</span>            6    555       <span style="text-decoration: underline;">2</span>445  0.185            0.815      <span style="text-decoration: underline;">3</span>000</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 7</span>            7    190       <span style="text-decoration: underline;">2</span>810  0.063<span style="text-decoration: underline;">3</span>           0.937      <span style="text-decoration: underline;">3</span>000</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 8</span>            8      0       <span style="text-decoration: underline;">3</span>000  0                1          <span style="text-decoration: underline;">3</span>000</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;"> 9</span>            9      1       <span style="text-decoration: underline;">2</span>999  0.000<span style="text-decoration: underline;">333</span>         1.00       <span style="text-decoration: underline;">3</span>000</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">10</span>           10      0       <span style="text-decoration: underline;">3</span>000  0                1          <span style="text-decoration: underline;">3</span>000</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">11</span>           11      0       <span style="text-decoration: underline;">3</span>000  0                1          <span style="text-decoration: underline;">3</span>000</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">12</span>           12    745       <span style="text-decoration: underline;">2</span>255  0.248            0.752      <span style="text-decoration: underline;">3</span>000</span></span>
-<span><span class="co">## <span style="color: #BCBCBC;">13</span>           13    432       <span style="text-decoration: underline;">1</span>268  0.254            0.746      <span style="text-decoration: underline;">1</span>700</span></span></code></pre>
-<div class="sourceCode" id="cb35"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/gg_miss_span.html">gg_miss_span</a></span><span class="op">(</span><span class="va">pedestrian</span>, <span class="va">hourly_counts</span>, span_every <span class="op">=</span> <span class="fl">3000</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/gg-miss-span-1.png" width="500" style="display: block; margin: auto;"></p>
-<div class="sourceCode" id="cb36"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="co"># works with the rest of ggplot</span></span>
-<span><span class="fu"><a href="../reference/gg_miss_span.html">gg_miss_span</a></span><span class="op">(</span><span class="va">pedestrian</span>, <span class="va">hourly_counts</span>, span_every <span class="op">=</span> <span class="fl">3000</span><span class="op">)</span> <span class="op">+</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span>x <span class="op">=</span> <span class="st">"custom"</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/gg-miss-span-2.png" width="500" style="display: block; margin: auto;"></p>
-<div class="sourceCode" id="cb37"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/gg_miss_span.html">gg_miss_span</a></span><span class="op">(</span><span class="va">pedestrian</span>, <span class="va">hourly_counts</span>, span_every <span class="op">=</span> <span class="fl">3000</span><span class="op">)</span> <span class="op">+</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_dark</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/gg-miss-span-3.png" width="500" style="display: block; margin: auto;"></p>
-<p>You can also explore <code>miss_var_span</code> by group with the
-<code>facet</code> argument.</p>
-<div class="sourceCode" id="cb38"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/gg_miss_span.html">gg_miss_span</a></span><span class="op">(</span><span class="va">pedestrian</span>, </span>
-<span>             <span class="va">hourly_counts</span>, </span>
-<span>             span_every <span class="op">=</span> <span class="fl">3000</span>, </span>
-<span>             facet <span class="op">=</span> <span class="va">sensor_name</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/gg-miss-span-group-1.png" width="500" style="display: block; margin: auto;"></p>
-</div>
-<div class="section level3">
-<h3 id="gg_miss_case_cumsum">
-<code>gg_miss_case_cumsum</code><a class="anchor" aria-label="anchor" href="#gg_miss_case_cumsum"></a>
-</h3>
-<p>This plot shows the cumulative sum of missing values, reading the
-rows of the dataset from the top to bottom. It is powered by the
-<code><a href="../reference/miss_case_cumsum.html">miss_case_cumsum()</a></code> function.</p>
-<div class="sourceCode" id="cb39"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/gg_miss_case_cumsum.html">gg_miss_case_cumsum</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/gg-miss-case-cumsum-1.png" width="500" style="display: block; margin: auto;"></p>
-<div class="sourceCode" id="cb40"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span>
-<span><span class="fu"><a href="../reference/gg_miss_case_cumsum.html">gg_miss_case_cumsum</a></span><span class="op">(</span><span class="va">riskfactors</span>, breaks <span class="op">=</span> <span class="fl">50</span><span class="op">)</span> <span class="op">+</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_bw</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/gg-miss-case-cumsum-2.png" width="500" style="display: block; margin: auto;"></p>
-</div>
-<div class="section level3">
-<h3 id="gg_miss_var_cumsum">
-<code>gg_miss_var_cumsum</code><a class="anchor" aria-label="anchor" href="#gg_miss_var_cumsum"></a>
-</h3>
-<p>This plot shows the cumulative sum of missing values, reading columns
-from the left to the right of your dataframe. It is powered by the
-<code><a href="../reference/miss_var_cumsum.html">miss_var_cumsum()</a></code> function.</p>
-<div class="sourceCode" id="cb41"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/gg_miss_var_cumsum.html">gg_miss_var_cumsum</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/gg-miss-var-cumsum-1.png" width="500" style="display: block; margin: auto;"></p>
-</div>
-<div class="section level3">
-<h3 id="gg_miss_which">
-<code>gg_miss_which</code><a class="anchor" aria-label="anchor" href="#gg_miss_which"></a>
-</h3>
-<p>This plot shows a set of rectangles that indicate whether there is a
-missing element in a column or not.</p>
-<div class="sourceCode" id="cb42"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/gg_miss_which.html">gg_miss_which</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></code></pre></div>
-<p><img src="naniar-visualisation_files/figure-html/gg-miss-which-1.png" width="500" style="display: block; margin: auto;"></p>
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diff --git a/docs/articles/naniar-visualisation_files/figure-html/gg-miss-case-1.png b/docs/articles/naniar-visualisation_files/figure-html/gg-miss-case-1.png
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diff --git a/docs/articles/replace-with-na.html b/docs/articles/replace-with-na.html
deleted file mode 100644
index 1475f755..00000000
--- a/docs/articles/replace-with-na.html
+++ /dev/null
@@ -1,467 +0,0 @@
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-      <img src="../logo.png" class="logo" alt=""><h1>Replacing values with NA</h1>
-                        <h4 data-toc-skip class="author">Nicholas
-Tierney</h4>
-            
-            <h4 data-toc-skip class="date">2023-05-01</h4>
-      
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/vignettes/replace-with-na.Rmd" class="external-link"><code>vignettes/replace-with-na.Rmd</code></a></small>
-      <div class="d-none name"><code>replace-with-na.Rmd</code></div>
-    </div>
-
-    
-    
-<p>When dealing with missing values, you might want to replace values
-with a missing values (<code>NA</code>). This is useful in cases when
-you know the origin of the data and can be certain which values should
-be missing. For example, you might know that all values of “N/A”, “N A”,
-and “Not Available”, or -99, or -1 are supposed to be missing.</p>
-<p><code>naniar</code> provides functions to specifically work on this
-type of problem using the function <code><a href="../reference/replace_with_na.html">replace_with_na()</a></code>. This
-function is the compliment to <code><a href="https://tidyr.tidyverse.org/reference/replace_na.html" class="external-link">tidyr::replace_na()</a></code>, which
-replaces an NA value with a specified value, whereas
-<code><a href="../reference/replace_with_na.html">naniar::replace_with_na()</a></code> replaces a value with an NA:</p>
-<ul>
-<li>
-<code><a href="https://tidyr.tidyverse.org/reference/replace_na.html" class="external-link">tidyr::replace_na()</a></code>: Missing values turns into a value
-(NA –&gt; -99)</li>
-<li>
-<code><a href="../reference/replace_with_na.html">naniar::replace_with_na()</a></code>: Value becomes a missing
-value (-99 –&gt; NA)</li>
-</ul>
-<p>In this vignette, we describe some simple use cases for these
-functions and describe how they work.</p>
-<div class="section level2">
-<h2 id="example-data">Example data<a class="anchor" aria-label="anchor" href="#example-data"></a>
-</h2>
-<p>First, we introduce a small fictional dataset, <code>df</code>, which
-contains some common features of a dataset with the sorts of missing
-values we might encounter. This includes multiple specifications of
-missing values, such as “N/A”, “N A”, and “Not Available”. And also some
-common numeric codes, like -98, -99, and -1.</p>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">df</span> <span class="op">&lt;-</span> <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/tribble.html" class="external-link">tribble</a></span><span class="op">(</span></span>
-<span>  <span class="op">~</span><span class="va">name</span>,           <span class="op">~</span><span class="va">x</span>,  <span class="op">~</span><span class="va">y</span>,              <span class="op">~</span><span class="va">z</span>,  </span>
-<span>  <span class="st">"N/A"</span>,           <span class="fl">1</span>,   <span class="st">"N/A"</span>,           <span class="op">-</span><span class="fl">100</span>, </span>
-<span>  <span class="st">"N A"</span>,           <span class="fl">3</span>,   <span class="st">"NOt available"</span>, <span class="op">-</span><span class="fl">99</span>,</span>
-<span>  <span class="st">"N / A"</span>,         <span class="cn">NA</span>,  <span class="st">"29"</span>,              <span class="op">-</span><span class="fl">98</span>,</span>
-<span>  <span class="st">"Not Available"</span>, <span class="op">-</span><span class="fl">99</span>, <span class="st">"25"</span>,              <span class="op">-</span><span class="fl">101</span>,</span>
-<span>  <span class="st">"John Smith"</span>,    <span class="op">-</span><span class="fl">98</span>, <span class="st">"28"</span>,              <span class="op">-</span><span class="fl">1</span><span class="op">)</span></span></code></pre></div>
-<div class="section level3">
-<h3 id="using-replace_with_na">Using <code>replace_with_na</code><a class="anchor" aria-label="anchor" href="#using-replace_with_na"></a>
-</h3>
-<p>What if we want to replace the value -99 in the <code>x</code> column
-with a missing value?</p>
-<p>First, let’s load <code>naniar</code>:</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/njtierney/naniar" class="external-link">naniar</a></span><span class="op">)</span></span></code></pre></div>
-<p>Now, we specify the fact that we want to replace -99 with a missing
-value. To do so we use the <code>replace</code> argument, and specify a
-named list, which contains the names of the variable and the value it
-would take to replace with <code>NA</code>.</p>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu"><a href="../reference/replace_with_na.html">replace_with_na</a></span><span class="op">(</span>replace <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>x <span class="op">=</span> <span class="op">-</span><span class="fl">99</span><span class="op">)</span><span class="op">)</span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 5 × 4</span></span></span>
-<span><span class="co">#&gt;   name              x y                 z</span></span>
-<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> N/A               1 N/A            -<span style="color: #BB0000;">100</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> N A               3 NOt available   -<span style="color: #BB0000;">99</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span> N / A            <span style="color: #BB0000;">NA</span> 29              -<span style="color: #BB0000;">98</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> Not Available    <span style="color: #BB0000;">NA</span> 25             -<span style="color: #BB0000;">101</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">5</span> John Smith      -<span style="color: #BB0000;">98</span> 28               -<span style="color: #BB0000;">1</span></span></span></code></pre></div>
-<p>And say we want to replace -98 as well?</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/replace_with_na.html">replace_with_na</a></span><span class="op">(</span>replace <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>x <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="op">-</span><span class="fl">99</span>, <span class="op">-</span><span class="fl">98</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 5 × 4</span></span></span>
-<span><span class="co">#&gt;   name              x y                 z</span></span>
-<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> N/A               1 N/A            -<span style="color: #BB0000;">100</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> N A               3 NOt available   -<span style="color: #BB0000;">99</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span> N / A            <span style="color: #BB0000;">NA</span> 29              -<span style="color: #BB0000;">98</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> Not Available    <span style="color: #BB0000;">NA</span> 25             -<span style="color: #BB0000;">101</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">5</span> John Smith       <span style="color: #BB0000;">NA</span> 28               -<span style="color: #BB0000;">1</span></span></span></code></pre></div>
-<p>And then what if we want to replace -99 and -98 in all the numeric
-columns, x and z?</p>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/replace_with_na.html">replace_with_na</a></span><span class="op">(</span>replace <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>x <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="op">-</span><span class="fl">99</span>,<span class="op">-</span><span class="fl">98</span><span class="op">)</span>,</span>
-<span>                             z <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="op">-</span><span class="fl">99</span>, <span class="op">-</span><span class="fl">98</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 5 × 4</span></span></span>
-<span><span class="co">#&gt;   name              x y                 z</span></span>
-<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> N/A               1 N/A            -<span style="color: #BB0000;">100</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> N A               3 NOt available    <span style="color: #BB0000;">NA</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span> N / A            <span style="color: #BB0000;">NA</span> 29               <span style="color: #BB0000;">NA</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> Not Available    <span style="color: #BB0000;">NA</span> 25             -<span style="color: #BB0000;">101</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">5</span> John Smith       <span style="color: #BB0000;">NA</span> 28               -<span style="color: #BB0000;">1</span></span></span></code></pre></div>
-<p>Using <code><a href="../reference/replace_with_na.html">replace_with_na()</a></code> works well when we know the
-exact value to be replaced, and for which variables we want to replace,
-providing there are not many variables. But what do you do when you’ve
-got many variables you want to observe?</p>
-</div>
-<div class="section level3">
-<h3 id="extending-replace_with_na">Extending <code>replace_with_na</code><a class="anchor" aria-label="anchor" href="#extending-replace_with_na"></a>
-</h3>
-<p>Sometimes you have many of the same value that you want to replace.
-For example, -99 and -98 above, and also the variants of “NA”, such as
-“N/A”, and “N / A”, and “Not Available”. You might also have certain
-variables that you want to be affected by these rules, or you might have
-more complex rules, like, “only affect variables that are numeric, or
-character, with this rule”.</p>
-<p>To account for these cases we have borrowed from <a href="https://dplyr.tidyverse.org/reference/scoped.html" class="external-link"><code>dplyr</code>’s
-scoped variants</a> and created the functions:</p>
-<ul>
-<li>
-<code><a href="../reference/replace_with_na_all.html">replace_with_na_all()</a></code> Replaces NA for all
-variables.</li>
-<li>
-<code><a href="../reference/replace_with_na_at.html">replace_with_na_at()</a></code> Replaces NA on a subset of
-variables specified with character quotes (e.g., c(“var1”,
-“var2”)).</li>
-<li>
-<code><a href="../reference/replace_with_na_if.html">replace_with_na_if()</a></code> Replaces NA based on applying an
-operation on the subset of variables for which a predicate function
-(is.numeric, is.character, etc) returns TRUE.</li>
-</ul>
-<p>Below we will now consider some very simple examples of the use of
-these functions, so that you can better understand how to use them.</p>
-</div>
-<div class="section level3">
-<h3 id="using-replace_with_na_all">Using <code>replace_with_na_all</code><a class="anchor" aria-label="anchor" href="#using-replace_with_na_all"></a>
-</h3>
-<p>Use <code><a href="../reference/replace_with_na_all.html">replace_with_na_all()</a></code> when you want to replace ALL
-values that meet a condition across an entire dataset. The syntax here
-is a little different, and follows the rules for rlang’s expression of
-simple functions. This means that the function starts with
-<code>~</code>, and when referencing a variable, you use
-<code>.x</code>.</p>
-<p>For example, if we want to replace all cases of -99 in our dataset,
-we write:</p>
-<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu"><a href="../reference/replace_with_na_all.html">replace_with_na_all</a></span><span class="op">(</span>condition <span class="op">=</span> <span class="op">~</span><span class="va">.x</span> <span class="op">==</span> <span class="op">-</span><span class="fl">99</span><span class="op">)</span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 5 × 4</span></span></span>
-<span><span class="co">#&gt;   name              x y                 z</span></span>
-<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> N/A               1 N/A            -<span style="color: #BB0000;">100</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> N A               3 NOt available    <span style="color: #BB0000;">NA</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span> N / A            <span style="color: #BB0000;">NA</span> 29              -<span style="color: #BB0000;">98</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> Not Available    <span style="color: #BB0000;">NA</span> 25             -<span style="color: #BB0000;">101</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">5</span> John Smith      -<span style="color: #BB0000;">98</span> 28               -<span style="color: #BB0000;">1</span></span></span></code></pre></div>
-<p>Likewise, if you have a set of (annoying) repeating strings like
-various spellings of “NA”, then I suggest you first lay out all the
-offending cases:</p>
-<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="co"># write out all the offending strings</span></span>
-<span><span class="va">na_strings</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"NA"</span>, <span class="st">"N A"</span>, <span class="st">"N / A"</span>, <span class="st">"N/A"</span>, <span class="st">"N/ A"</span>, <span class="st">"Not Available"</span>, <span class="st">"NOt available"</span><span class="op">)</span></span></code></pre></div>
-<p>Then you write <code>~.x %in% na_strings</code> - which reads as
-“does this value occur in the list of NA strings”.</p>
-<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/replace_with_na_all.html">replace_with_na_all</a></span><span class="op">(</span>condition <span class="op">=</span> <span class="op">~</span><span class="va">.x</span> <span class="op"><a href="https://rdrr.io/r/base/match.html" class="external-link">%in%</a></span> <span class="va">na_strings</span><span class="op">)</span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 5 × 4</span></span></span>
-<span><span class="co">#&gt;   name           x y         z</span></span>
-<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> <span style="color: #BB0000;">NA</span>             1 <span style="color: #BB0000;">NA</span>     -<span style="color: #BB0000;">100</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> <span style="color: #BB0000;">NA</span>             3 <span style="color: #BB0000;">NA</span>      -<span style="color: #BB0000;">99</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span> <span style="color: #BB0000;">NA</span>            <span style="color: #BB0000;">NA</span> 29      -<span style="color: #BB0000;">98</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> <span style="color: #BB0000;">NA</span>           -<span style="color: #BB0000;">99</span> 25     -<span style="color: #BB0000;">101</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">5</span> John Smith   -<span style="color: #BB0000;">98</span> 28       -<span style="color: #BB0000;">1</span></span></span></code></pre></div>
-<p>You can also use the built-in strings and numbers in naniar:</p>
-<ul>
-<li><code>common_na_numbers</code></li>
-<li><code>common_na_strings</code></li>
-</ul>
-<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">common_na_numbers</span></span>
-<span><span class="co">#&gt; [1]    -9   -99  -999 -9999  9999    66    77    88</span></span>
-<span><span class="va">common_na_strings</span></span>
-<span><span class="co">#&gt;  [1] "missing" "NA"      "N A"     "N/A"     "#N/A"    "NA "     " NA"    </span></span>
-<span><span class="co">#&gt;  [8] "N /A"    "N / A"   " N / A"  "N / A "  "na"      "n a"     "n/a"    </span></span>
-<span><span class="co">#&gt; [15] "na "     " na"     "n /a"    "n / a"   " a / a"  "n / a "  "NULL"   </span></span>
-<span><span class="co">#&gt; [22] "null"    ""        "\\?"     "\\*"     "\\."</span></span></code></pre></div>
-<p>And you can replace values matching those strings or numbers like
-so:</p>
-<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/replace_with_na_all.html">replace_with_na_all</a></span><span class="op">(</span>condition <span class="op">=</span> <span class="op">~</span><span class="va">.x</span> <span class="op"><a href="https://rdrr.io/r/base/match.html" class="external-link">%in%</a></span> <span class="va">common_na_strings</span><span class="op">)</span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 5 × 4</span></span></span>
-<span><span class="co">#&gt;   name              x y                 z</span></span>
-<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> <span style="color: #BB0000;">NA</span>                1 <span style="color: #BB0000;">NA</span>             -<span style="color: #BB0000;">100</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> <span style="color: #BB0000;">NA</span>                3 NOt available   -<span style="color: #BB0000;">99</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span> <span style="color: #BB0000;">NA</span>               <span style="color: #BB0000;">NA</span> 29              -<span style="color: #BB0000;">98</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> Not Available   -<span style="color: #BB0000;">99</span> 25             -<span style="color: #BB0000;">101</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">5</span> John Smith      -<span style="color: #BB0000;">98</span> 28               -<span style="color: #BB0000;">1</span></span></span></code></pre></div>
-<div class="section level4">
-<h4 id="replace_with_na_at">
-<code>replace_with_na_at</code><a class="anchor" aria-label="anchor" href="#replace_with_na_at"></a>
-</h4>
-<p>This is similar to <code>_all</code>, but instead in this case you
-can specify the variables that you want affected by the rule that you
-state. This is useful in cases where you want to specify a rule that
-only affects a selected number of variables.</p>
-<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> </span>
-<span>  <span class="fu"><a href="../reference/replace_with_na_at.html">replace_with_na_at</a></span><span class="op">(</span>.vars <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"x"</span>,<span class="st">"z"</span><span class="op">)</span>,</span>
-<span>                     condition <span class="op">=</span> <span class="op">~</span><span class="va">.x</span> <span class="op">==</span> <span class="op">-</span><span class="fl">99</span><span class="op">)</span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 5 × 4</span></span></span>
-<span><span class="co">#&gt;   name              x y                 z</span></span>
-<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> N/A               1 N/A            -<span style="color: #BB0000;">100</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> N A               3 NOt available    <span style="color: #BB0000;">NA</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span> N / A            <span style="color: #BB0000;">NA</span> 29              -<span style="color: #BB0000;">98</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> Not Available    <span style="color: #BB0000;">NA</span> 25             -<span style="color: #BB0000;">101</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">5</span> John Smith      -<span style="color: #BB0000;">98</span> 28               -<span style="color: #BB0000;">1</span></span></span></code></pre></div>
-<p>Although you can achieve this with regular
-<code><a href="../reference/replace_with_na.html">replace_with_na()</a></code>, it is more concise to use,
-<code><a href="../reference/replace_with_na_at.html">replace_with_na_at()</a></code>. Additionally, you can specify rules
-as function, for example, make a value NA if the exponent of that number
-is less than 1:</p>
-<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> </span>
-<span>  <span class="fu"><a href="../reference/replace_with_na_at.html">replace_with_na_at</a></span><span class="op">(</span>.vars <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"x"</span>,<span class="st">"z"</span><span class="op">)</span>,</span>
-<span>                     condition <span class="op">=</span> <span class="op">~</span> <span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">exp</a></span><span class="op">(</span><span class="va">.x</span><span class="op">)</span> <span class="op">&lt;</span> <span class="fl">1</span><span class="op">)</span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 5 × 4</span></span></span>
-<span><span class="co">#&gt;   name              x y                 z</span></span>
-<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> N/A               1 N/A              <span style="color: #BB0000;">NA</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> N A               3 NOt available    <span style="color: #BB0000;">NA</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span> N / A            <span style="color: #BB0000;">NA</span> 29               <span style="color: #BB0000;">NA</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> Not Available    <span style="color: #BB0000;">NA</span> 25               <span style="color: #BB0000;">NA</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">5</span> John Smith       <span style="color: #BB0000;">NA</span> 28               <span style="color: #BB0000;">NA</span></span></span></code></pre></div>
-</div>
-<div class="section level4">
-<h4 id="replace_with_na_if">
-<code>replace_with_na_if</code><a class="anchor" aria-label="anchor" href="#replace_with_na_if"></a>
-</h4>
-<p>There may be some cases where you can identify variables based on
-some test - <code><a href="https://rdrr.io/r/base/character.html" class="external-link">is.character()</a></code> - are they character variables?
-<code><a href="https://rdrr.io/r/base/numeric.html" class="external-link">is.numeric()</a></code> - Are they numeric or double? and a given
-value inside that type of data. For example,</p>
-<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/replace_with_na_if.html">replace_with_na_if</a></span><span class="op">(</span>.predicate <span class="op">=</span> <span class="va">is.character</span>,</span>
-<span>                     condition <span class="op">=</span> <span class="op">~</span><span class="va">.x</span> <span class="op"><a href="https://rdrr.io/r/base/match.html" class="external-link">%in%</a></span> <span class="op">(</span><span class="st">"N/A"</span><span class="op">)</span><span class="op">)</span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 5 × 4</span></span></span>
-<span><span class="co">#&gt;   name              x y                 z</span></span>
-<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> <span style="color: #BB0000;">NA</span>                1 <span style="color: #BB0000;">NA</span>             -<span style="color: #BB0000;">100</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> N A               3 NOt available   -<span style="color: #BB0000;">99</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span> N / A            <span style="color: #BB0000;">NA</span> 29              -<span style="color: #BB0000;">98</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> Not Available   -<span style="color: #BB0000;">99</span> 25             -<span style="color: #BB0000;">101</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">5</span> John Smith      -<span style="color: #BB0000;">98</span> 28               -<span style="color: #BB0000;">1</span></span></span>
-<span></span>
-<span><span class="co"># or</span></span>
-<span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/replace_with_na_if.html">replace_with_na_if</a></span><span class="op">(</span>.predicate <span class="op">=</span> <span class="va">is.character</span>,</span>
-<span>                     condition <span class="op">=</span> <span class="op">~</span><span class="va">.x</span> <span class="op"><a href="https://rdrr.io/r/base/match.html" class="external-link">%in%</a></span> <span class="op">(</span><span class="va">na_strings</span><span class="op">)</span><span class="op">)</span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 5 × 4</span></span></span>
-<span><span class="co">#&gt;   name           x y         z</span></span>
-<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> <span style="color: #BB0000;">NA</span>             1 <span style="color: #BB0000;">NA</span>     -<span style="color: #BB0000;">100</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> <span style="color: #BB0000;">NA</span>             3 <span style="color: #BB0000;">NA</span>      -<span style="color: #BB0000;">99</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span> <span style="color: #BB0000;">NA</span>            <span style="color: #BB0000;">NA</span> 29      -<span style="color: #BB0000;">98</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> <span style="color: #BB0000;">NA</span>           -<span style="color: #BB0000;">99</span> 25     -<span style="color: #BB0000;">101</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">5</span> John Smith   -<span style="color: #BB0000;">98</span> 28       -<span style="color: #BB0000;">1</span></span></span></code></pre></div>
-<p>This means that you are able to apply a rule to many variables that
-meet a pre-specified condition. This can be of particular use if you
-have many variables and don’t want to list them all, and also if you
-know that there is a particular problem for variables of a particular
-class.</p>
-</div>
-</div>
-</div>
-<div class="section level2">
-<h2 id="notes-on-alternative-ways-to-handle-replacing-with-nas">Notes on alternative ways to handle replacing with NAs<a class="anchor" aria-label="anchor" href="#notes-on-alternative-ways-to-handle-replacing-with-nas"></a>
-</h2>
-<p>There are some alternative ways to handle replacing values with NA in
-the tidyverse, <code>na_if</code> and using <code>readr</code>. These
-are ultimately not as expressive as the <code><a href="../reference/replace_with_na.html">replace_with_na()</a></code>
-functions, but they are very useful if you only have one kind of value
-to replace with a missing, and if you know what the missing values are
-upon reading in the data.</p>
-<p><strong><code><a href="https://dplyr.tidyverse.org/reference/na_if.html" class="external-link">dplyr::na_if</a></code></strong></p>
-<p>This function allows you to replace exact values - similar to
-<code><a href="../reference/replace_with_na.html">replace_with_na()</a></code>, but only for one single column in a data
-frame. Here is how you would use it in our examples.</p>
-<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="co"># instead of:</span></span>
-<span><span class="va">df_1</span> <span class="op">&lt;-</span> <span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu"><a href="../reference/replace_with_na_all.html">replace_with_na_all</a></span><span class="op">(</span>condition <span class="op">=</span> <span class="op">~</span><span class="va">.x</span> <span class="op">==</span> <span class="op">-</span><span class="fl">99</span><span class="op">)</span></span>
-<span><span class="va">df_1</span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 5 × 4</span></span></span>
-<span><span class="co">#&gt;   name              x y                 z</span></span>
-<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> N/A               1 N/A            -<span style="color: #BB0000;">100</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> N A               3 NOt available    <span style="color: #BB0000;">NA</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span> N / A            <span style="color: #BB0000;">NA</span> 29              -<span style="color: #BB0000;">98</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> Not Available    <span style="color: #BB0000;">NA</span> 25             -<span style="color: #BB0000;">101</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">5</span> John Smith      -<span style="color: #BB0000;">98</span> 28               -<span style="color: #BB0000;">1</span></span></span>
-<span></span>
-<span><span class="va">df_2</span> <span class="op">&lt;-</span> <span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span></span>
-<span>  x <span class="op">=</span> <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/na_if.html" class="external-link">na_if</a></span><span class="op">(</span><span class="va">x</span>, <span class="op">-</span><span class="fl">99</span><span class="op">)</span>,</span>
-<span>  y <span class="op">=</span> <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/na_if.html" class="external-link">na_if</a></span><span class="op">(</span><span class="va">z</span>, <span class="op">-</span><span class="fl">99</span><span class="op">)</span></span>
-<span><span class="op">)</span></span>
-<span><span class="va">df_2</span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 5 × 4</span></span></span>
-<span><span class="co">#&gt;   name              x     y     z</span></span>
-<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> N/A               1  -<span style="color: #BB0000;">100</span>  -<span style="color: #BB0000;">100</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> N A               3    <span style="color: #BB0000;">NA</span>   -<span style="color: #BB0000;">99</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span> N / A            <span style="color: #BB0000;">NA</span>   -<span style="color: #BB0000;">98</span>   -<span style="color: #BB0000;">98</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> Not Available    <span style="color: #BB0000;">NA</span>  -<span style="color: #BB0000;">101</span>  -<span style="color: #BB0000;">101</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">5</span> John Smith      -<span style="color: #BB0000;">98</span>    -<span style="color: #BB0000;">1</span>    -<span style="color: #BB0000;">1</span></span></span>
-<span></span>
-<span><span class="co"># are they the same?</span></span>
-<span><span class="fu"><a href="https://rdrr.io/r/base/all.equal.html" class="external-link">all.equal</a></span><span class="op">(</span><span class="va">df_1</span>, <span class="va">df_2</span><span class="op">)</span></span>
-<span><span class="co">#&gt; [1] "Component \"y\": Modes: character, numeric"                       </span></span>
-<span><span class="co">#&gt; [2] "Component \"y\": target is character, current is numeric"         </span></span>
-<span><span class="co">#&gt; [3] "Component \"z\": 'is.NA' value mismatch: 0 in current 1 in target"</span></span></code></pre></div>
-<p>Note, however, that <code><a href="https://dplyr.tidyverse.org/reference/na_if.html" class="external-link">na_if()</a></code> can only take arguments of
-length one. This means that it cannot capture other statements like</p>
-<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">na_strings</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"NA"</span>, <span class="st">"N A"</span>, <span class="st">"N / A"</span>, <span class="st">"N/A"</span>, <span class="st">"N/ A"</span>, <span class="st">"Not Available"</span>, <span class="st">"NOt available"</span><span class="op">)</span></span>
-<span><span class="va">df_3</span> <span class="op">&lt;-</span> <span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu"><a href="../reference/replace_with_na_all.html">replace_with_na_all</a></span><span class="op">(</span>condition <span class="op">=</span> <span class="op">~</span><span class="va">.x</span> <span class="op"><a href="https://rdrr.io/r/base/match.html" class="external-link">%in%</a></span> <span class="va">na_strings</span><span class="op">)</span></span></code></pre></div>
-<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="co"># Not run:</span></span>
-<span><span class="va">df_4</span> <span class="op">&lt;-</span> <span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/na_if.html" class="external-link">na_if</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">.</span>, y <span class="op">=</span> <span class="va">na_strings</span><span class="op">)</span></span>
-<span><span class="co"># Error in check_length(y, x, fmt_args("y"), glue("same as {fmt_args(~x)}")) : </span></span>
-<span>  <span class="co"># argument "y" is missing, with no default</span></span></code></pre></div>
-<p>It also cannot handle more complex equations, where you want to refer
-to values in other columns, or values less than or greater than another
-value.</p>
-<p><strong>catch NAs with <code>readr</code></strong></p>
-<p>When reading in your data, you can use the <code>na</code> argument
-inside <code>readr</code> to replace certain values with NA. For
-example:</p>
-<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="co"># not run</span></span>
-<span><span class="va">dat_raw</span> <span class="op">&lt;-</span> <span class="fu">readr</span><span class="fu">::</span><span class="fu"><a href="https://readr.tidyverse.org/reference/read_delim.html" class="external-link">read_csv</a></span><span class="op">(</span><span class="st">"original.csv"</span>, na <span class="op">=</span> <span class="va">na_strings</span><span class="op">)</span></span></code></pre></div>
-<p>This would convert all of the values in <code>na_strings</code> into
-missing values.</p>
-<p>This is useful to use if you happen to know the NA types upon reading
-in the data. However, this is not always practical in a data analysis
-pipeline.</p>
-</div>
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-      <img src="../logo.png" class="logo" alt=""><h1>Special Missing Values</h1>
-                        <h4 data-toc-skip class="author">Nicholas
-Tierney</h4>
-            
-            <h4 data-toc-skip class="date">2023-05-01</h4>
-      
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/vignettes/special-missing-values.Rmd" class="external-link"><code>vignettes/special-missing-values.Rmd</code></a></small>
-      <div class="d-none name"><code>special-missing-values.Rmd</code></div>
-    </div>
-
-    
-    
-<p>Data sometimes have special missing values to indicate specific
-reasons for missingness. For example, “9999” is sometimes used in
-weather data, say for for example, the <a href="https://www.ncei.noaa.gov/products/land-based-station/global-historical-climatology-network-daily" class="external-link">Global
-Historical Climate Network (GHCN) data</a>, to indicate specific types
-of missingness, such as instrument failure.</p>
-<p>You might be interested in creating your own special missing values
-so that you can mark specific, known reasons for missingness. For
-example, an individual dropping out of a study, known instrument failure
-in weather instruments, or for values being censored in analysis. In
-these cases, the data is missing, but we have information about
-<em>why</em> it is missing. Coding these cases as <code>NA</code> would
-cause us to lose this valuable information. Other stats programming
-languages like STATA, SAS, and SPSS have this capacity, but currently
-<code>R</code> does not. So, we need a way to create these special
-missing values.</p>
-<p>We can use <code>recode_shadow</code> to recode missingness by
-recoding the special missing value as something like
-<code>NA_reason</code>. <code>naniar</code> records these values in the
-<code>shadow</code> part of <code>nabular</code> data, which is a
-special dataframe that contains missingness information.</p>
-<p>This vignette describes how to add special missing values using the
-<code><a href="../reference/recode_shadow.html">recode_shadow()</a></code> function. First we consider some
-terminology to explain these ideas, if you are not familiar with the
-workflows in <code>naniar</code>.</p>
-<div class="section level2">
-<h2 id="terminology">Terminology<a class="anchor" aria-label="anchor" href="#terminology"></a>
-</h2>
-<p>Missing data can be represented as a binary matrix of “missing” or
-“not missing”, which in <code>naniar</code> we call a “shadow matrix”, a
-term borrowed from <a href="https://www.researchgate.net/publication/2758672_Missing_Data_in_Interactive_High-Dimensional_Data_Visualization" class="external-link">Swayne
-and Buja, 1998</a>.</p>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/njtierney/naniar" class="external-link">naniar</a></span><span class="op">)</span></span>
-<span><span class="fu"><a href="../reference/as_shadow.html">as_shadow</a></span><span class="op">(</span><span class="va">oceanbuoys</span><span class="op">)</span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 736 × 8</span></span></span>
-<span><span class="co">#&gt;    year_NA latitude_NA longitude_NA sea_temp_c_NA air_temp_c_NA humidity_NA</span></span>
-<span><span class="co">#&gt;    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>       <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>        <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>      </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 1</span> !NA     !NA         !NA          !NA           !NA           !NA        </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 2</span> !NA     !NA         !NA          !NA           !NA           !NA        </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 3</span> !NA     !NA         !NA          !NA           !NA           !NA        </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 4</span> !NA     !NA         !NA          !NA           !NA           !NA        </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 5</span> !NA     !NA         !NA          !NA           !NA           !NA        </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 6</span> !NA     !NA         !NA          !NA           !NA           !NA        </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 7</span> !NA     !NA         !NA          !NA           !NA           !NA        </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span> !NA     !NA         !NA          !NA           !NA           !NA        </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span> !NA     !NA         !NA          !NA           !NA           !NA        </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span> !NA     !NA         !NA          !NA           !NA           !NA        </span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 726 more rows</span></span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 2 more variables: wind_ew_NA &lt;fct&gt;, wind_ns_NA &lt;fct&gt;</span></span></span></code></pre></div>
-<p>The <code>shadow matrix</code> has three key features to facilitate
-analysis</p>
-<ol style="list-style-type: decimal">
-<li><p>Coordinated names: Variables in the shadow matrix gain the same
-name as in the data, with the suffix “_NA”.</p></li>
-<li><p>Special missing values: Values in the shadow matrix can be
-“special” missing values, indicated as <code>NA_suffix</code>, where
-“suffix” is a very short message of the type of missings.</p></li>
-<li><p>Cohesiveness: Binding the shadow matrix column-wise to the
-original data creates a cohesive “nabular” data form, useful for
-visualization and summaries.</p></li>
-</ol>
-<p>We create <code>nabular</code> data by <code>bind</code>ing the
-shadow to the data:</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/bind_shadow.html">bind_shadow</a></span><span class="op">(</span><span class="va">oceanbuoys</span><span class="op">)</span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 736 × 16</span></span></span>
-<span><span class="co">#&gt;     year latitude longitude sea_temp_c air_temp_c humidity wind_ew wind_ns</span></span>
-<span><span class="co">#&gt;    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 1</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       27.6       27.1     79.6   -<span style="color: #BB0000;">6.40</span>    5.40</span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 2</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       27.5       27.0     75.8   -<span style="color: #BB0000;">5.30</span>    5.30</span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 3</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       27.6       27       76.5   -<span style="color: #BB0000;">5.10</span>    4.5 </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 4</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       27.6       26.9     76.2   -<span style="color: #BB0000;">4.90</span>    2.5 </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 5</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       27.6       26.8     76.4   -<span style="color: #BB0000;">3.5</span>     4.10</span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 6</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       27.8       26.9     76.7   -<span style="color: #BB0000;">4.40</span>    1.60</span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 7</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       28.0       27.0     76.5   -<span style="color: #BB0000;">2</span>       3.5 </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       28.0       27.1     78.3   -<span style="color: #BB0000;">3.70</span>    4.5 </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       28.0       27.2     78.6   -<span style="color: #BB0000;">4.20</span>    5   </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span>  <span style="text-decoration: underline;">1</span>997        0      -<span style="color: #BB0000;">110</span>       28.0       27.2     76.9   -<span style="color: #BB0000;">3.60</span>    3.5 </span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 726 more rows</span></span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 8 more variables: year_NA &lt;fct&gt;, latitude_NA &lt;fct&gt;, longitude_NA &lt;fct&gt;,</span></span></span>
-<span><span class="co">#&gt; <span style="color: #949494;">#   sea_temp_c_NA &lt;fct&gt;, air_temp_c_NA &lt;fct&gt;, humidity_NA &lt;fct&gt;,</span></span></span>
-<span><span class="co">#&gt; <span style="color: #949494;">#   wind_ew_NA &lt;fct&gt;, wind_ns_NA &lt;fct&gt;</span></span></span></code></pre></div>
-<p>This keeps the data values tied to their missingness, and has great
-benefits for exploring missing and imputed values in data. See the
-vignettes <a href="http://naniar.njtierney.com/articles/getting-started-w-naniar.html">Getting
-Started with naniar</a> and <a href="http://naniar.njtierney.com/articles/exploring-imputed-values.html">Exploring
-Imputations with naniar</a> for more details.</p>
-</div>
-<div class="section level2">
-<h2 id="recoding-missing-values">Recoding missing values<a class="anchor" aria-label="anchor" href="#recoding-missing-values"></a>
-</h2>
-<p>To demonstrate recoding of missing values, we use a toy dataset,
-<code>dat</code>:</p>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">df</span> <span class="op">&lt;-</span> <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/tribble.html" class="external-link">tribble</a></span><span class="op">(</span></span>
-<span><span class="op">~</span><span class="va">wind</span>, <span class="op">~</span><span class="va">temp</span>,</span>
-<span><span class="op">-</span><span class="fl">99</span>,    <span class="fl">45</span>,</span>
-<span><span class="fl">68</span>,    <span class="cn">NA</span>,</span>
-<span><span class="fl">72</span>,    <span class="fl">25</span></span>
-<span><span class="op">)</span></span>
-<span></span>
-<span><span class="va">df</span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 3 × 2</span></span></span>
-<span><span class="co">#&gt;    wind  temp</span></span>
-<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span>   -<span style="color: #BB0000;">99</span>    45</span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span>    68    <span style="color: #BB0000;">NA</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span>    72    25</span></span></code></pre></div>
-<p>To recode the value -99 as a missing value “broken_machine”, we first
-create nabular data with <code>bind_shadow</code>:</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">dfs</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/bind_shadow.html">bind_shadow</a></span><span class="op">(</span><span class="va">df</span><span class="op">)</span></span>
-<span></span>
-<span><span class="va">dfs</span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 3 × 4</span></span></span>
-<span><span class="co">#&gt;    wind  temp wind_NA temp_NA</span></span>
-<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>  </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span>   -<span style="color: #BB0000;">99</span>    45 !NA     !NA    </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span>    68    <span style="color: #BB0000;">NA</span> !NA     NA     </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span>    72    25 !NA     !NA</span></span></code></pre></div>
-<p>Special types of missingness are encoded in the shadow part nabular
-data, using the <code>recode_shadow</code> function, we can recode the
-missing values like so:</p>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">dfs_recode</span> <span class="op">&lt;-</span> <span class="va">dfs</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> </span>
-<span>  <span class="fu"><a href="../reference/recode_shadow.html">recode_shadow</a></span><span class="op">(</span>wind <span class="op">=</span> <span class="fu"><a href="../reference/where.html">.where</a></span><span class="op">(</span><span class="va">wind</span> <span class="op">==</span> <span class="op">-</span><span class="fl">99</span> <span class="op">~</span> <span class="st">"broken_machine"</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
-<p>This reads as “recode shadow for wind where wind is equal to -99, and
-give it the label”broken_machine”. The <code>.where</code> function is
-used to help make our intent clearer, and reads very much like the
-<code><a href="https://dplyr.tidyverse.org/reference/case_when.html" class="external-link">dplyr::case_when()</a></code> function, but takes care of encoding
-extra factor levels into the missing data.</p>
-<p>The extra types of missingness are recoded in the shadow part of the
-nabular data as additional factor levels:</p>
-<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/levels.html" class="external-link">levels</a></span><span class="op">(</span><span class="va">dfs_recode</span><span class="op">$</span><span class="va">wind_NA</span><span class="op">)</span></span>
-<span><span class="co">#&gt; [1] "!NA"               "NA"                "NA_broken_machine"</span></span>
-<span><span class="fu"><a href="https://rdrr.io/r/base/levels.html" class="external-link">levels</a></span><span class="op">(</span><span class="va">dfs_recode</span><span class="op">$</span><span class="va">temp_NA</span><span class="op">)</span></span>
-<span><span class="co">#&gt; [1] "!NA"               "NA"                "NA_broken_machine"</span></span></code></pre></div>
-<p>All additional types of missingness are recorded across all shadow
-variables, even if those variables don’t contain that special missing
-value. This ensures all flavours of missingness are known.</p>
-<p>To summarise, to use <code>recode_shadow</code>, the user provides
-the following information:</p>
-<ul>
-<li>A variable that they want to effect
-(<code>recode_shadow(var = ...)</code>)</li>
-<li>A condition that they want to implement
-(<code>.where(condition ~ ...)</code>)</li>
-<li>A suffix for the new type of missing value
-(<code>.where(condition ~ suffix)</code>)</li>
-</ul>
-<p>Under the hood, this special missing value is recoded as a new factor
-level in the shadow matrix, so that every column is aware of all
-possible new values of missingness.</p>
-<p>Some examples of using <code>recode_shadow</code> in a workflow will
-be discussed in more detail in the near future, for the moment, here is
-a recommended workflow:</p>
-<ul>
-<li>Use <code><a href="../reference/recode_shadow.html">recode_shadow()</a></code> with actual data</li>
-<li>Replacing the previous actual values using
-<code><a href="../reference/replace_with_na.html">replace_with_na()</a></code> (see the vignette on <a href="http://naniar.njtierney.com/articles/replace-with-na.html">replacing
-values with NA</a>)</li>
-<li>Explore missings where special cases are considered</li>
-<li>Explore imputed values, looking at these special cases</li>
-</ul>
-</div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
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diff --git a/docs/authors.html b/docs/authors.html
deleted file mode 100644
index 353e0679..00000000
--- a/docs/authors.html
+++ /dev/null
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-      <img src="logo.png" class="logo" alt=""><h1>Authors and Citation</h1>
-    </div>
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-    <div class="section level2 citation">
-      <h2>Authors</h2>
-      
-      <ul class="list-unstyled"><li>
-          <p><strong>Nicholas Tierney</strong>. Author, maintainer. <a href="https://orcid.org/https://orcid.org/0000-0003-1460-8722" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
-          </p>
-        </li>
-        <li>
-          <p><strong><a href="http://www.dicook.org/" class="external-link">Di Cook</a></strong>. Author. <a href="https://orcid.org/https://orcid.org/0000-0002-3813-7155" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
-          </p>
-        </li>
-        <li>
-          <p><strong><a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a></strong>. Author. <a href="https://orcid.org/https://orcid.org/0000-0003-2865-2548" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
-          </p>
-        </li>
-        <li>
-          <p><strong><a href="https://colinfay.me/" class="external-link">Colin Fay</a></strong>. Author. <a href="https://orcid.org/https://orcid.org/0000-0001-7343-1846" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
-          </p>
-        </li>
-        <li>
-          <p><strong>Mitchell O'Hara-Wild</strong>. Contributor. 
-          </p>
-        </li>
-        <li>
-          <p><strong>Jim Hester</strong>. Contributor. 
-          </p>
-        </li>
-        <li>
-          <p><strong>Luke Smith</strong>. Contributor. 
-          </p>
-        </li>
-        <li>
-          <p><strong>Andrew Heiss</strong>. Contributor. <a href="https://orcid.org/https://orcid.org/0000-0002-3948-3914" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
-          </p>
-        </li>
-      </ul></div>
-
-    <div class="section level2 citation">
-      <h2 id="citation">Citation</h2>
-      <p><small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/inst/CITATION" class="external-link"><code>inst/CITATION</code></a></small></p>
-
-      <p>Tierney N, Cook D (2023).
-“Expanding Tidy Data Principles to Facilitate Missing Data Exploration, Visualization and Assessment of Imputations.”
-<em>Journal of Statistical Software</em>, <b>105</b>(7), 1–31.
-<a href="https://doi.org/10.18637/jss.v105.i07" class="external-link">doi:10.18637/jss.v105.i07</a>. 
-</p>
-      <pre>@Article{,
-  title = {Expanding Tidy Data Principles to Facilitate Missing Data Exploration, Visualization and Assessment of Imputations},
-  author = {Nicholas Tierney and Dianne Cook},
-  journal = {Journal of Statistical Software},
-  year = {2023},
-  volume = {105},
-  number = {7},
-  pages = {1--31},
-  doi = {10.18637/jss.v105.i07},
-}</pre>
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-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
-</div>
-
-    </footer></div>
-
-  
-
-  
-
-  </body></html>
-
diff --git a/docs/docsearch.css b/docs/docsearch.css
deleted file mode 100644
index e5f1fe1d..00000000
--- a/docs/docsearch.css
+++ /dev/null
@@ -1,148 +0,0 @@
-/* Docsearch -------------------------------------------------------------- */
-/*
-  Source: https://github.com/algolia/docsearch/
-  License: MIT
-*/
-
-.algolia-autocomplete {
-  display: block;
-  -webkit-box-flex: 1;
-  -ms-flex: 1;
-  flex: 1
-}
-
-.algolia-autocomplete .ds-dropdown-menu {
-  width: 100%;
-  min-width: none;
-  max-width: none;
-  padding: .75rem 0;
-  background-color: #fff;
-  background-clip: padding-box;
-  border: 1px solid rgba(0, 0, 0, .1);
-  box-shadow: 0 .5rem 1rem rgba(0, 0, 0, .175);
-}
-
-@media (min-width:768px) {
-  .algolia-autocomplete .ds-dropdown-menu {
-      width: 175%
-  }
-}
-
-.algolia-autocomplete .ds-dropdown-menu::before {
-  display: none
-}
-
-.algolia-autocomplete .ds-dropdown-menu [class^=ds-dataset-] {
-  padding: 0;
-  background-color: rgb(255,255,255);
-  border: 0;
-  max-height: 80vh;
-}
-
-.algolia-autocomplete .ds-dropdown-menu .ds-suggestions {
-  margin-top: 0
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion {
-  padding: 0;
-  overflow: visible
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--category-header {
-  padding: .125rem 1rem;
-  margin-top: 0;
-  font-size: 1.3em;
-  font-weight: 500;
-  color: #00008B;
-  border-bottom: 0
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--wrapper {
-    float: none;
-    padding-top: 0
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--subcategory-column {
-  float: none;
-  width: auto;
-  padding: 0;
-  text-align: left
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--content {
-  float: none;
-  width: auto;
-  padding: 0
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--content::before {
-  display: none
-}
-
-.algolia-autocomplete .ds-suggestion:not(:first-child) .algolia-docsearch-suggestion--category-header {
-  padding-top: .75rem;
-  margin-top: .75rem;
-  border-top: 1px solid rgba(0, 0, 0, .1)
-}
-
-.algolia-autocomplete .ds-suggestion .algolia-docsearch-suggestion--subcategory-column {
-  display: block;
-  padding: .1rem 1rem;
-  margin-bottom: 0.1;
-  font-size: 1.0em;
-  font-weight: 400
-  /* display: none */
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--title {
-  display: block;
-  padding: .25rem 1rem;
-  margin-bottom: 0;
-  font-size: 0.9em;
-  font-weight: 400
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--text {
-  padding: 0 1rem .5rem;
-  margin-top: -.25rem;
-  font-size: 0.8em;
-  font-weight: 400;
-  line-height: 1.25
-}
-
-.algolia-autocomplete .algolia-docsearch-footer {
-  width: 110px;
-  height: 20px;
-  z-index: 3;
-  margin-top: 10.66667px;
-  float: right;
-  font-size: 0;
-  line-height: 0;
-}
-
-.algolia-autocomplete .algolia-docsearch-footer--logo {
-  background-image: url("data:image/svg+xml;utf8,<svg viewBox='0 0 130 18' xmlns='http://www.w3.org/2000/svg'><defs><linearGradient x1='-36.868%' y1='134.936%' x2='129.432%' y2='-27.7%' id='a'><stop stop-color='%2300AEFF' offset='0%'/><stop stop-color='%233369E7' offset='100%'/></linearGradient></defs><g fill='none' fill-rule='evenodd'><path d='M59.399.022h13.299a2.372 2.372 0 0 1 2.377 2.364V15.62a2.372 2.372 0 0 1-2.377 2.364H59.399a2.372 2.372 0 0 1-2.377-2.364V2.381A2.368 2.368 0 0 1 59.399.022z' fill='url(%23a)'/><path d='M66.257 4.56c-2.815 0-5.1 2.272-5.1 5.078 0 2.806 2.284 5.072 5.1 5.072 2.815 0 5.1-2.272 5.1-5.078 0-2.806-2.279-5.072-5.1-5.072zm0 8.652c-1.983 0-3.593-1.602-3.593-3.574 0-1.972 1.61-3.574 3.593-3.574 1.983 0 3.593 1.602 3.593 3.574a3.582 3.582 0 0 1-3.593 3.574zm0-6.418v2.664c0 .076.082.131.153.093l2.377-1.226c.055-.027.071-.093.044-.147a2.96 2.96 0 0 0-2.465-1.487c-.055 0-.11.044-.11.104l.001-.001zm-3.33-1.956l-.312-.311a.783.783 0 0 0-1.106 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-  background-repeat: no-repeat;
-  background-position: 50%;
-  background-size: 100%;
-  overflow: hidden;
-  text-indent: -9000px;
-  width: 100%;
-  height: 100%;
-  display: block;
-  transform: translate(-8px);
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--highlight {
-  color: #FF8C00;
-  background: rgba(232, 189, 54, 0.1)
-}
-
-
-.algolia-autocomplete .algolia-docsearch-suggestion--text .algolia-docsearch-suggestion--highlight {
-  box-shadow: inset 0 -2px 0 0 rgba(105, 105, 105, .5)
-}
-
-.algolia-autocomplete .ds-suggestion.ds-cursor .algolia-docsearch-suggestion--content {
-  background-color: rgba(192, 192, 192, .15)
-}
diff --git a/docs/docsearch.js b/docs/docsearch.js
deleted file mode 100644
index b35504cd..00000000
--- a/docs/docsearch.js
+++ /dev/null
@@ -1,85 +0,0 @@
-$(function() {
-
-  // register a handler to move the focus to the search bar
-  // upon pressing shift + "/" (i.e. "?")
-  $(document).on('keydown', function(e) {
-    if (e.shiftKey && e.keyCode == 191) {
-      e.preventDefault();
-      $("#search-input").focus();
-    }
-  });
-
-  $(document).ready(function() {
-    // do keyword highlighting
-    /* modified from https://jsfiddle.net/julmot/bL6bb5oo/ */
-    var mark = function() {
-
-      var referrer = document.URL ;
-      var paramKey = "q" ;
-
-      if (referrer.indexOf("?") !== -1) {
-        var qs = referrer.substr(referrer.indexOf('?') + 1);
-        var qs_noanchor = qs.split('#')[0];
-        var qsa = qs_noanchor.split('&');
-        var keyword = "";
-
-        for (var i = 0; i < qsa.length; i++) {
-          var currentParam = qsa[i].split('=');
-
-          if (currentParam.length !== 2) {
-            continue;
-          }
-
-          if (currentParam[0] == paramKey) {
-            keyword = decodeURIComponent(currentParam[1].replace(/\+/g, "%20"));
-          }
-        }
-
-        if (keyword !== "") {
-          $(".contents").unmark({
-            done: function() {
-              $(".contents").mark(keyword);
-            }
-          });
-        }
-      }
-    };
-
-    mark();
-  });
-});
-
-/* Search term highlighting ------------------------------*/
-
-function matchedWords(hit) {
-  var words = [];
-
-  var hierarchy = hit._highlightResult.hierarchy;
-  // loop to fetch from lvl0, lvl1, etc.
-  for (var idx in hierarchy) {
-    words = words.concat(hierarchy[idx].matchedWords);
-  }
-
-  var content = hit._highlightResult.content;
-  if (content) {
-    words = words.concat(content.matchedWords);
-  }
-
-  // return unique words
-  var words_uniq = [...new Set(words)];
-  return words_uniq;
-}
-
-function updateHitURL(hit) {
-
-  var words = matchedWords(hit);
-  var url = "";
-
-  if (hit.anchor) {
-    url = hit.url_without_anchor + '?q=' + escape(words.join(" ")) + '#' + hit.anchor;
-  } else {
-    url = hit.url + '?q=' + escape(words.join(" "));
-  }
-
-  return url;
-}
diff --git a/docs/docsearch.json b/docs/docsearch.json
deleted file mode 100644
index 996da0d9..00000000
--- a/docs/docsearch.json
+++ /dev/null
@@ -1,95 +0,0 @@
-{
-  "index_name": "naniar",
-  "start_urls": [
-    {
-      "url": "http://naniar.njtierney.com//index.html",
-      "selectors_key": "homepage",
-      "tags": [
-        "homepage"
-      ]
-    },
-    {
-      "url": "http://naniar.njtierney.com//reference",
-      "selectors_key": "reference",
-      "tags": [
-        "reference"
-      ]
-    },
-    {
-      "url": "http://naniar.njtierney.com//articles",
-      "selectors_key": "articles",
-      "tags": [
-        "articles"
-      ]
-    }
-  ],
-  "stop_urls": [
-    "/reference/$",
-    "/reference/index.html",
-    "/articles/$",
-    "/articles/index.html"
-  ],
-  "sitemap_urls": [
-    "http://naniar.njtierney.com//sitemap.xml"
-  ],
-  "selectors": {
-    "homepage": {
-      "lvl0": {
-        "selector": ".contents h1",
-        "default_value": "naniar Home page"
-      },
-      "lvl1": {
-        "selector": ".contents h2"
-      },
-      "lvl2": {
-        "selector": ".contents h3",
-        "default_value": "Context"
-      },
-      "lvl3": ".ref-arguments td, .ref-description",
-      "text": ".contents p, .contents li, .contents .pre"
-    },
-    "reference": {
-      "lvl0": {
-        "selector": ".contents h1"
-      },
-      "lvl1": {
-        "selector": ".contents .name",
-        "default_value": "Argument"
-      },
-      "lvl2": {
-        "selector": ".ref-arguments th",
-        "default_value": "Description"
-      },
-      "lvl3": ".ref-arguments td, .ref-description",
-      "text": ".contents p, .contents li"
-    },
-    "articles": {
-      "lvl0": {
-        "selector": ".contents h1"
-      },
-      "lvl1": {
-        "selector": ".contents .name"
-      },
-      "lvl2": {
-        "selector": ".contents h2, .contents h3",
-        "default_value": "Context"
-      },
-      "text": ".contents p, .contents li, .tempate-article .contents .pre"
-    }
-  },
-  "selectors_exclude": [
-    ".dont-index"
-    ],
-  "min_indexed_level": 2,
-  "custom_settings": {
-    "separatorsToIndex": "_",
-    "attributesToRetrieve": [
-      "hierarchy",
-      "content",
-      "anchor",
-      "url",
-      "url_without_anchor"
-    ]
-  }
-}
-
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-<meta name="description" content="Missing values are ubiquitous in data and need to be explored and
-    handled in the initial stages of analysis. naniar provides data 
-    structures and functions that facilitate the plotting of missing values and 
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-    explored with minimal deviation from the common work patterns of ggplot2 
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-<meta property="og:description" content="Missing values are ubiquitous in data and need to be explored and
-    handled in the initial stages of analysis. naniar provides data 
-    structures and functions that facilitate the plotting of missing values and 
-    examination of imputations. This allows missing data dependencies to be 
-    explored with minimal deviation from the common work patterns of ggplot2 
-    and tidy data. The work is fully discussed at Tierney &amp; Cook (2023) 
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-<img src="logo.png" class="logo" alt=""><h1 id="naniar-">naniar 
-<a class="anchor" aria-label="anchor" href="#naniar-"></a>
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-<p><code>naniar</code> provides principled, tidy ways to summarise, visualise, and manipulate missing data with minimal deviations from the workflows in ggplot2 and tidy data. It does this by providing:</p>
-<ul>
-<li>Shadow matrices, a tidy data structure for missing data:
-<ul>
-<li>
-<code><a href="reference/bind_shadow.html">bind_shadow()</a></code> and <code><a href="reference/nabular.html">nabular()</a></code>
-</li>
-</ul>
-</li>
-<li>Shorthand summaries for missing data:
-<ul>
-<li>
-<code><a href="reference/n_miss.html">n_miss()</a></code> and <code><a href="reference/n_complete.html">n_complete()</a></code>
-</li>
-<li>
-<code><a href="reference/pct_miss.html">pct_miss()</a></code>and <code><a href="reference/pct_complete.html">pct_complete()</a></code>
-</li>
-</ul>
-</li>
-<li>Numerical summaries of missing data in variables and cases:
-<ul>
-<li>
-<code><a href="reference/miss_var_summary.html">miss_var_summary()</a></code> and <code><a href="reference/miss_var_table.html">miss_var_table()</a></code>
-</li>
-<li>
-<code><a href="reference/miss_case_summary.html">miss_case_summary()</a></code>, <code><a href="reference/miss_case_table.html">miss_case_table()</a></code>
-</li>
-</ul>
-</li>
-<li>Statistical tests of missingness:
-<ul>
-<li>
-<code><a href="reference/mcar_test.html">mcar_test()</a></code> for <a href="https://doi.org/10.1080/01621459.1988.10478722" class="external-link">Little’s (1988)</a> missing completely at random (MCAR) test</li>
-</ul>
-</li>
-<li>Visualisation for missing data:
-<ul>
-<li><code><a href="reference/geom_miss_point.html">geom_miss_point()</a></code></li>
-<li><code><a href="reference/gg_miss_var.html">gg_miss_var()</a></code></li>
-<li><code><a href="reference/gg_miss_case.html">gg_miss_case()</a></code></li>
-<li><code><a href="reference/gg_miss_fct.html">gg_miss_fct()</a></code></li>
-</ul>
-</li>
-</ul>
-<p>For more details on the workflow and theory underpinning naniar, read the vignette <a href="https://naniar.njtierney.com/articles/getting-started-w-naniar.html" class="external-link">Getting started with naniar</a>.</p>
-<p>For a short primer on the data visualisation available in naniar, read the vignette <a href="https://naniar.njtierney.com/articles/naniar-visualisation.html" class="external-link">Gallery of Missing Data Visualisations</a>.</p>
-<p>For full details of the package, including</p>
-</div>
-<div class="section level1">
-<h1 id="installation">Installation<a class="anchor" aria-label="anchor" href="#installation"></a>
-</h1>
-<p>You can install naniar from CRAN:</p>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html" class="external-link">install.packages</a></span><span class="op">(</span><span class="st">"naniar"</span><span class="op">)</span></span></code></pre></div>
-<p>Or you can install the development version on github using <code>remotes</code>:</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="co"># install.packages("remotes")</span></span>
-<span><span class="fu">remotes</span><span class="fu">::</span><span class="fu"><a href="https://remotes.r-lib.org/reference/install_github.html" class="external-link">install_github</a></span><span class="op">(</span><span class="st">"njtierney/naniar"</span><span class="op">)</span></span></code></pre></div>
-</div>
-<div class="section level1">
-<h1 id="a-short-overview-of-naniar">A short overview of naniar<a class="anchor" aria-label="anchor" href="#a-short-overview-of-naniar"></a>
-</h1>
-<p>Visualising missing data might sound a little strange - how do you visualise something that is not there? One approach to visualising missing data comes from <a href="http://ggobi.org/" class="external-link">ggobi</a> and <a href="https://www.swmath.org/software/3067" class="external-link">manet</a>, which replaces <code>NA</code> values with values 10% lower than the minimum value in that variable. This visualisation is provided with the <code><a href="reference/geom_miss_point.html">geom_miss_point()</a></code> ggplot2 geom, which we illustrate by exploring the relationship between Ozone and Solar radiation from the airquality dataset.</p>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">airquality</span>,</span>
-<span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Ozone</span>,</span>
-<span>           y <span class="op">=</span> <span class="va">Solar.R</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_point.html" class="external-link">geom_point</a></span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="co">#&gt; Warning: Removed 42 rows containing missing values (`geom_point()`).</span></span></code></pre></div>
-<p><img src="reference/figures/README-regular-geom-point-1.png"><!-- --></p>
-<p>ggplot2 does not handle these missing values, and we get a warning message about the missing values.</p>
-<p>We can instead use <code><a href="reference/geom_miss_point.html">geom_miss_point()</a></code> to display the missing data</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/njtierney/naniar" class="external-link">naniar</a></span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">airquality</span>,</span>
-<span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Ozone</span>,</span>
-<span>           y <span class="op">=</span> <span class="va">Solar.R</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="reference/geom_miss_point.html">geom_miss_point</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-<p><img src="reference/figures/README-geom-miss-point-1.png"><!-- --></p>
-<p><code><a href="reference/geom_miss_point.html">geom_miss_point()</a></code> has shifted the missing values to now be 10% below the minimum value. The missing values are a different colour so that missingness becomes pre-attentive. As it is a ggplot2 geom, it supports features like faceting and other ggplot features.</p>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">p1</span> <span class="op">&lt;-</span></span>
-<span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">airquality</span>,</span>
-<span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Ozone</span>,</span>
-<span>           y <span class="op">=</span> <span class="va">Solar.R</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="reference/geom_miss_point.html">geom_miss_point</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/facet_wrap.html" class="external-link">facet_wrap</a></span><span class="op">(</span><span class="op">~</span><span class="va">Month</span>, ncol <span class="op">=</span> <span class="fl">2</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/theme.html" class="external-link">theme</a></span><span class="op">(</span>legend.position <span class="op">=</span> <span class="st">"bottom"</span><span class="op">)</span></span>
-<span></span>
-<span><span class="va">p1</span></span></code></pre></div>
-<p><img src="reference/figures/README-facet-by-month-1.png"><!-- --></p>
-</div>
-<div class="section level1">
-<h1 id="data-structures">Data Structures<a class="anchor" aria-label="anchor" href="#data-structures"></a>
-</h1>
-<p>naniar provides a data structure for working with missing data, the shadow matrix <a href="https://www.researchgate.net/publication/2758672_Missing_Data_in_Interactive_High-Dimensional_Data_Visualization" class="external-link">(Swayne and Buja, 1998)</a>. The shadow matrix is the same dimension as the data, and consists of binary indicators of missingness of data values, where missing is represented as “NA”, and not missing is represented as “!NA”, and variable names are kep the same, with the added suffix “_NA” to the variables.</p>
-<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span>
-<span><span class="co">#&gt;   Ozone Solar.R Wind Temp Month Day</span></span>
-<span><span class="co">#&gt; 1    41     190  7.4   67     5   1</span></span>
-<span><span class="co">#&gt; 2    36     118  8.0   72     5   2</span></span>
-<span><span class="co">#&gt; 3    12     149 12.6   74     5   3</span></span>
-<span><span class="co">#&gt; 4    18     313 11.5   62     5   4</span></span>
-<span><span class="co">#&gt; 5    NA      NA 14.3   56     5   5</span></span>
-<span><span class="co">#&gt; 6    28      NA 14.9   66     5   6</span></span>
-<span></span>
-<span><span class="fu"><a href="reference/as_shadow.html">as_shadow</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span>
-<span><span class="co">#&gt; # A tibble: 153 × 6</span></span>
-<span><span class="co">#&gt;    Ozone_NA Solar.R_NA Wind_NA Temp_NA Month_NA Day_NA</span></span>
-<span><span class="co">#&gt;    &lt;fct&gt;    &lt;fct&gt;      &lt;fct&gt;   &lt;fct&gt;   &lt;fct&gt;    &lt;fct&gt; </span></span>
-<span><span class="co">#&gt;  1 !NA      !NA        !NA     !NA     !NA      !NA   </span></span>
-<span><span class="co">#&gt;  2 !NA      !NA        !NA     !NA     !NA      !NA   </span></span>
-<span><span class="co">#&gt;  3 !NA      !NA        !NA     !NA     !NA      !NA   </span></span>
-<span><span class="co">#&gt;  4 !NA      !NA        !NA     !NA     !NA      !NA   </span></span>
-<span><span class="co">#&gt;  5 NA       NA         !NA     !NA     !NA      !NA   </span></span>
-<span><span class="co">#&gt;  6 !NA      NA         !NA     !NA     !NA      !NA   </span></span>
-<span><span class="co">#&gt;  7 !NA      !NA        !NA     !NA     !NA      !NA   </span></span>
-<span><span class="co">#&gt;  8 !NA      !NA        !NA     !NA     !NA      !NA   </span></span>
-<span><span class="co">#&gt;  9 !NA      !NA        !NA     !NA     !NA      !NA   </span></span>
-<span><span class="co">#&gt; 10 NA       !NA        !NA     !NA     !NA      !NA   </span></span>
-<span><span class="co">#&gt; # ℹ 143 more rows</span></span></code></pre></div>
-<p>Binding the shadow data to the data you help keep better track of the missing values. This format is called “nabular”, a portmanteau of <code>NA</code> and <code>tabular</code>. You can bind the shadow to the data using <code>bind_shadow</code> or <code>nabular</code>:</p>
-<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="reference/bind_shadow.html">bind_shadow</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span>
-<span><span class="co">#&gt; # A tibble: 153 × 12</span></span>
-<span><span class="co">#&gt;    Ozone Solar.R  Wind  Temp Month   Day Ozone_NA Solar.R_NA Wind_NA Temp_NA</span></span>
-<span><span class="co">#&gt;    &lt;int&gt;   &lt;int&gt; &lt;dbl&gt; &lt;int&gt; &lt;int&gt; &lt;int&gt; &lt;fct&gt;    &lt;fct&gt;      &lt;fct&gt;   &lt;fct&gt;  </span></span>
-<span><span class="co">#&gt;  1    41     190   7.4    67     5     1 !NA      !NA        !NA     !NA    </span></span>
-<span><span class="co">#&gt;  2    36     118   8      72     5     2 !NA      !NA        !NA     !NA    </span></span>
-<span><span class="co">#&gt;  3    12     149  12.6    74     5     3 !NA      !NA        !NA     !NA    </span></span>
-<span><span class="co">#&gt;  4    18     313  11.5    62     5     4 !NA      !NA        !NA     !NA    </span></span>
-<span><span class="co">#&gt;  5    NA      NA  14.3    56     5     5 NA       NA         !NA     !NA    </span></span>
-<span><span class="co">#&gt;  6    28      NA  14.9    66     5     6 !NA      NA         !NA     !NA    </span></span>
-<span><span class="co">#&gt;  7    23     299   8.6    65     5     7 !NA      !NA        !NA     !NA    </span></span>
-<span><span class="co">#&gt;  8    19      99  13.8    59     5     8 !NA      !NA        !NA     !NA    </span></span>
-<span><span class="co">#&gt;  9     8      19  20.1    61     5     9 !NA      !NA        !NA     !NA    </span></span>
-<span><span class="co">#&gt; 10    NA     194   8.6    69     5    10 NA       !NA        !NA     !NA    </span></span>
-<span><span class="co">#&gt; # ℹ 143 more rows</span></span>
-<span><span class="co">#&gt; # ℹ 2 more variables: Month_NA &lt;fct&gt;, Day_NA &lt;fct&gt;</span></span>
-<span><span class="fu"><a href="reference/nabular.html">nabular</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span>
-<span><span class="co">#&gt; # A tibble: 153 × 12</span></span>
-<span><span class="co">#&gt;    Ozone Solar.R  Wind  Temp Month   Day Ozone_NA Solar.R_NA Wind_NA Temp_NA</span></span>
-<span><span class="co">#&gt;    &lt;int&gt;   &lt;int&gt; &lt;dbl&gt; &lt;int&gt; &lt;int&gt; &lt;int&gt; &lt;fct&gt;    &lt;fct&gt;      &lt;fct&gt;   &lt;fct&gt;  </span></span>
-<span><span class="co">#&gt;  1    41     190   7.4    67     5     1 !NA      !NA        !NA     !NA    </span></span>
-<span><span class="co">#&gt;  2    36     118   8      72     5     2 !NA      !NA        !NA     !NA    </span></span>
-<span><span class="co">#&gt;  3    12     149  12.6    74     5     3 !NA      !NA        !NA     !NA    </span></span>
-<span><span class="co">#&gt;  4    18     313  11.5    62     5     4 !NA      !NA        !NA     !NA    </span></span>
-<span><span class="co">#&gt;  5    NA      NA  14.3    56     5     5 NA       NA         !NA     !NA    </span></span>
-<span><span class="co">#&gt;  6    28      NA  14.9    66     5     6 !NA      NA         !NA     !NA    </span></span>
-<span><span class="co">#&gt;  7    23     299   8.6    65     5     7 !NA      !NA        !NA     !NA    </span></span>
-<span><span class="co">#&gt;  8    19      99  13.8    59     5     8 !NA      !NA        !NA     !NA    </span></span>
-<span><span class="co">#&gt;  9     8      19  20.1    61     5     9 !NA      !NA        !NA     !NA    </span></span>
-<span><span class="co">#&gt; 10    NA     194   8.6    69     5    10 NA       !NA        !NA     !NA    </span></span>
-<span><span class="co">#&gt; # ℹ 143 more rows</span></span>
-<span><span class="co">#&gt; # ℹ 2 more variables: Month_NA &lt;fct&gt;, Day_NA &lt;fct&gt;</span></span></code></pre></div>
-<p>Using the nabular format helps you manage where missing values are in your dataset and make it easy to do visualisations where you split by missingness:</p>
-<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="reference/bind_shadow.html">bind_shadow</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Temp</span>,</span>
-<span>             fill <span class="op">=</span> <span class="va">Ozone_NA</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_density.html" class="external-link">geom_density</a></span><span class="op">(</span>alpha <span class="op">=</span> <span class="fl">0.5</span><span class="op">)</span></span></code></pre></div>
-<p><img src="reference/figures/README-shadow-w-ggplot-1.png"><!-- --></p>
-<p>And even visualise imputations</p>
-<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="reference/bind_shadow.html">bind_shadow</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/r/base/as.data.frame.html" class="external-link">as.data.frame</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> </span>
-<span>   <span class="fu">simputation</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/simputation/man/impute_lm.html" class="external-link">impute_lm</a></span><span class="op">(</span><span class="va">Ozone</span> <span class="op">~</span> <span class="va">Temp</span> <span class="op">+</span> <span class="va">Solar.R</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Solar.R</span>,</span>
-<span>             y <span class="op">=</span> <span class="va">Ozone</span>,</span>
-<span>             colour <span class="op">=</span> <span class="va">Ozone_NA</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span> </span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_point.html" class="external-link">geom_point</a></span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="co">#&gt; Warning: Removed 7 rows containing missing values (`geom_point()`).</span></span></code></pre></div>
-<p><img src="reference/figures/README-shadow-impute-1.png"><!-- --></p>
-<p>Or perform an <a href="https://www.nature.com/articles/nmeth.3033" class="external-link">upset</a> plot - to plot of the combinations of missingness across cases, using the <code>gg_miss_upset</code> function</p>
-<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="fu"><a href="reference/gg_miss_upset.html">gg_miss_upset</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></code></pre></div>
-<p><img src="reference/figures/README-gg-miss-upset-1.png"><!-- --></p>
-<p>naniar does this while following consistent principles that are easy to read, thanks to the tools of the tidyverse.</p>
-<p>naniar also provides handy visualations for each variable:</p>
-<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="fu"><a href="reference/gg_miss_var.html">gg_miss_var</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></code></pre></div>
-<p><img src="reference/figures/README-gg-miss-var-1.png"><!-- --></p>
-<p>Or the number of missings in a given variable at a repeating span</p>
-<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="reference/gg_miss_span.html">gg_miss_span</a></span><span class="op">(</span><span class="va">pedestrian</span>,</span>
-<span>             var <span class="op">=</span> <span class="va">hourly_counts</span>,</span>
-<span>             span_every <span class="op">=</span> <span class="fl">1500</span><span class="op">)</span></span></code></pre></div>
-<p><img src="reference/figures/README-gg-miss-span-1.png"><!-- --></p>
-<p>You can read about all of the visualisations in naniar in the vignette <a href="https://naniar.njtierney.com/articles/naniar-visualisation.html" class="external-link">Gallery of missing data visualisations using naniar</a>.</p>
-<p>naniar also provides handy helpers for calculating the number, proportion, and percentage of missing and complete observations:</p>
-<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="reference/n_miss.html">n_miss</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span>
-<span><span class="co">#&gt; [1] 44</span></span>
-<span><span class="fu"><a href="reference/n_complete.html">n_complete</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span>
-<span><span class="co">#&gt; [1] 874</span></span>
-<span><span class="fu"><a href="reference/prop_miss.html">prop_miss</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span>
-<span><span class="co">#&gt; [1] 0.04793028</span></span>
-<span><span class="fu"><a href="reference/prop_complete.html">prop_complete</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span>
-<span><span class="co">#&gt; [1] 0.9520697</span></span>
-<span><span class="fu"><a href="reference/pct_miss.html">pct_miss</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span>
-<span><span class="co">#&gt; [1] 4.793028</span></span>
-<span><span class="fu"><a href="reference/pct_complete.html">pct_complete</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span>
-<span><span class="co">#&gt; [1] 95.20697</span></span></code></pre></div>
-</div>
-<div class="section level1">
-<h1 id="numerical-summaries-for-missing-data">Numerical summaries for missing data<a class="anchor" aria-label="anchor" href="#numerical-summaries-for-missing-data"></a>
-</h1>
-<p>naniar provides numerical summaries of missing data, that follow a consistent rule that uses a syntax begining with <code>miss_</code>. Summaries focussing on variables or a single selected variable, start with <code>miss_var_</code>, and summaries for cases (the initial collected row order of the data), they start with <code>miss_case_</code>. All of these functions that return dataframes also work with dplyr’s <code><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by()</a></code>.</p>
-<p>For example, we can look at the number and percent of missings in each case and variable with <code><a href="reference/miss_var_summary.html">miss_var_summary()</a></code>, and <code><a href="reference/miss_case_summary.html">miss_case_summary()</a></code>, which both return output ordered by the number of missing values.</p>
-<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="fu"><a href="reference/miss_var_summary.html">miss_var_summary</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span>
-<span><span class="co">#&gt; # A tibble: 6 × 3</span></span>
-<span><span class="co">#&gt;   variable n_miss pct_miss</span></span>
-<span><span class="co">#&gt;   &lt;chr&gt;     &lt;int&gt;    &lt;num&gt;</span></span>
-<span><span class="co">#&gt; 1 Ozone        37    24.2 </span></span>
-<span><span class="co">#&gt; 2 Solar.R       7     4.58</span></span>
-<span><span class="co">#&gt; 3 Wind          0     0   </span></span>
-<span><span class="co">#&gt; 4 Temp          0     0   </span></span>
-<span><span class="co">#&gt; 5 Month         0     0   </span></span>
-<span><span class="co">#&gt; 6 Day           0     0</span></span>
-<span><span class="fu"><a href="reference/miss_case_summary.html">miss_case_summary</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span>
-<span><span class="co">#&gt; # A tibble: 153 × 3</span></span>
-<span><span class="co">#&gt;     case n_miss pct_miss</span></span>
-<span><span class="co">#&gt;    &lt;int&gt;  &lt;int&gt;    &lt;dbl&gt;</span></span>
-<span><span class="co">#&gt;  1     5      2     33.3</span></span>
-<span><span class="co">#&gt;  2    27      2     33.3</span></span>
-<span><span class="co">#&gt;  3     6      1     16.7</span></span>
-<span><span class="co">#&gt;  4    10      1     16.7</span></span>
-<span><span class="co">#&gt;  5    11      1     16.7</span></span>
-<span><span class="co">#&gt;  6    25      1     16.7</span></span>
-<span><span class="co">#&gt;  7    26      1     16.7</span></span>
-<span><span class="co">#&gt;  8    32      1     16.7</span></span>
-<span><span class="co">#&gt;  9    33      1     16.7</span></span>
-<span><span class="co">#&gt; 10    34      1     16.7</span></span>
-<span><span class="co">#&gt; # ℹ 143 more rows</span></span></code></pre></div>
-<p>You could also <code><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by()</a></code> to work out the number of missings in each variable across the levels within it.</p>
-<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span>
-<span><span class="co">#&gt; </span></span>
-<span><span class="co">#&gt; Attaching package: 'dplyr'</span></span>
-<span><span class="co">#&gt; The following objects are masked from 'package:stats':</span></span>
-<span><span class="co">#&gt; </span></span>
-<span><span class="co">#&gt;     filter, lag</span></span>
-<span><span class="co">#&gt; The following objects are masked from 'package:base':</span></span>
-<span><span class="co">#&gt; </span></span>
-<span><span class="co">#&gt;     intersect, setdiff, setequal, union</span></span>
-<span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">Month</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="reference/miss_var_summary.html">miss_var_summary</a></span><span class="op">(</span><span class="op">)</span></span>
-<span><span class="co">#&gt; # A tibble: 25 × 4</span></span>
-<span><span class="co">#&gt; # Groups:   Month [5]</span></span>
-<span><span class="co">#&gt;    Month variable n_miss pct_miss</span></span>
-<span><span class="co">#&gt;    &lt;int&gt; &lt;chr&gt;     &lt;int&gt;    &lt;num&gt;</span></span>
-<span><span class="co">#&gt;  1     5 Ozone         5     16.1</span></span>
-<span><span class="co">#&gt;  2     5 Solar.R       4     12.9</span></span>
-<span><span class="co">#&gt;  3     5 Wind          0      0  </span></span>
-<span><span class="co">#&gt;  4     5 Temp          0      0  </span></span>
-<span><span class="co">#&gt;  5     5 Day           0      0  </span></span>
-<span><span class="co">#&gt;  6     6 Ozone        21     70  </span></span>
-<span><span class="co">#&gt;  7     6 Solar.R       0      0  </span></span>
-<span><span class="co">#&gt;  8     6 Wind          0      0  </span></span>
-<span><span class="co">#&gt;  9     6 Temp          0      0  </span></span>
-<span><span class="co">#&gt; 10     6 Day           0      0  </span></span>
-<span><span class="co">#&gt; # ℹ 15 more rows</span></span></code></pre></div>
-<p>You can read more about all of these functions in the vignette <a href="https://naniar.njtierney.com/articles/getting-started-w-naniar.html" class="external-link">“Getting Started with naniar”</a>.</p>
-</div>
-<div class="section level1">
-<h1 id="statistical-tests-of-missingness">Statistical tests of missingness<a class="anchor" aria-label="anchor" href="#statistical-tests-of-missingness"></a>
-</h1>
-<p>naniar provides <code><a href="reference/mcar_test.html">mcar_test()</a></code> for <a href="https://doi.org/10.1080/01621459.1988.10478722" class="external-link">Little’s (1988)</a> statistical test for missing completely at random (MCAR) data. The null hypothesis in this test is that the data is MCAR, and the test statistic is a chi-squared value. Given the high statistic value and low p-value, we can conclude that the <code>airquality</code> data is not missing completely at random:</p>
-<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="reference/mcar_test.html">mcar_test</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span>
-<span><span class="co">#&gt; # A tibble: 1 × 4</span></span>
-<span><span class="co">#&gt;   statistic    df p.value missing.patterns</span></span>
-<span><span class="co">#&gt;       &lt;dbl&gt; &lt;dbl&gt;   &lt;dbl&gt;            &lt;int&gt;</span></span>
-<span><span class="co">#&gt; 1      35.1    14 0.00142                4</span></span></code></pre></div>
-</div>
-<div class="section level1">
-<h1 id="contributions">Contributions<a class="anchor" aria-label="anchor" href="#contributions"></a>
-</h1>
-<p>Please note that this project is released with a <a href="https://naniar.njtierney.com/CONDUCT.html" class="external-link">Contributor Code of Conduct</a>. By participating in this project you agree to abide by its terms.</p>
-</div>
-<div class="section level1">
-<h1 id="future-work">Future Work<a class="anchor" aria-label="anchor" href="#future-work"></a>
-</h1>
-<ul>
-<li>Extend the <code>geom_miss_*</code> family to include categorical variables, Bivariate plots: scatterplots, density overlays</li>
-<li>SQL translation for databases</li>
-<li>Big Data tools (sparklyr, sparklingwater)</li>
-<li>Work well with other imputation engines / processes</li>
-<li>Provide tools for assessing goodness of fit for classical approaches of MCAR, MAR, and MNAR (graphical inference from <code>nullabor</code> package)</li>
-</ul>
-<div class="section level2">
-<h2 id="acknowledgements">Acknowledgements<a class="anchor" aria-label="anchor" href="#acknowledgements"></a>
-</h2>
-<p>Firstly, thanks to <a href="https://github.com/dicook" class="external-link">Di Cook</a> for giving the initial inspiration for the package and laying down the rich theory and literature that the work in naniar is built upon. Naming credit (once again!) goes to <a href="https://github.com/milesmcbain" class="external-link">Miles McBain</a>. Among various other things, Miles also worked out how to overload the missing data and make it work as a geom. Thanks also to <a href="https://github.com/ColinFay" class="external-link">Colin Fay</a> for helping me understand tidy evaluation and for features such as <code>replace_to_na</code>, <code>miss_*_cumsum</code>, and more.</p>
-</div>
-<div class="section level2">
-<h2 id="a-note-on-the-name">A note on the name<a class="anchor" aria-label="anchor" href="#a-note-on-the-name"></a>
-</h2>
-<p>naniar was previously named <code>ggmissing</code> and initially provided a ggplot geom and some other visualisations. <code>ggmissing</code> was changed to <code>naniar</code> to reflect the fact that this package is going to be bigger in scope, and is not just related to <code>ggplot2</code>. Specifically, the package is designed to provide a suite of tools for generating visualisations of missing values and imputations, manipulate, and summarise missing data.</p>
-<blockquote>
-<p>…But <em>why</em> naniar?</p>
-</blockquote>
-<p>Well, I think it is useful to think of missing values in data being like this other dimension, perhaps like <a href="https://en.wikipedia.org/wiki/The_Chronicles_of_Narnia" class="external-link">C.S. Lewis’s Narnia</a> - a different world, hidden away. You go inside, and sometimes it seems like you’ve spent no time in there but time has passed very quickly, or the opposite. Also, <code>NA</code>niar = na in r, and if you so desire, naniar may sound like “noneoya” in an nz/aussie accent. Full credit to @MilesMcbain for the name, and @Hadley for the rearranged spelling.</p>
-</div>
-</div>
-
-  </main><aside class="col-md-3"><div class="links">
-<h2 data-toc-skip>Links</h2>
-<ul class="list-unstyled">
-<li><a href="https://cloud.r-project.org/package=naniar" class="external-link">View on CRAN</a></li>
-<li><a href="https://github.com/njtierney/naniar/" class="external-link">Browse source code</a></li>
-<li><a href="https://github.com/njtierney/naniar/issues" class="external-link">Report a bug</a></li>
-<li><a href="https://github.com/njtierney/naniar" class="external-link">Learn more</a></li>
-</ul>
-</div>
-
-<div class="license">
-<h2 data-toc-skip>License</h2>
-<ul class="list-unstyled">
-<li>
-<a href="https://opensource.org/licenses/mit-license.php" class="external-link">MIT</a> + file <a href="LICENSE-text.html">LICENSE</a>
-</li>
-</ul>
-</div>
-
-<div class="community">
-<h2 data-toc-skip>Community</h2>
-<ul class="list-unstyled">
-<li><a href="CONTRIBUTING.html">Contributing guide</a></li>
-</ul>
-</div>
-
-<div class="citation">
-<h2 data-toc-skip>Citation</h2>
-<ul class="list-unstyled">
-<li><a href="authors.html#citation">Citing naniar</a></li>
-</ul>
-</div>
-
-<div class="developers">
-<h2 data-toc-skip>Developers</h2>
-<ul class="list-unstyled">
-<li>Nicholas Tierney <br><small class="roles"> Author, maintainer </small> <a href="https://orcid.org/https://orcid.org/0000-0003-1460-8722" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a> </li>
-<li>
-<a href="http://www.dicook.org/" class="external-link">Di Cook</a> <br><small class="roles"> Author </small> <a href="https://orcid.org/https://orcid.org/0000-0002-3813-7155" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a> </li>
-<li>
-<a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a> <br><small class="roles"> Author </small> <a href="https://orcid.org/https://orcid.org/0000-0003-2865-2548" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a> </li>
-<li>
-<a href="https://colinfay.me/" class="external-link">Colin Fay</a> <br><small class="roles"> Author </small> <a href="https://orcid.org/https://orcid.org/0000-0001-7343-1846" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a> </li>
-<li><a href="authors.html">More about authors...</a></li>
-</ul>
-</div>
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-<div class="dev-status">
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diff --git a/docs/news/index.html b/docs/news/index.html
deleted file mode 100644
index b74e2b23..00000000
--- a/docs/news/index.html
+++ /dev/null
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-      <img src="../logo.png" class="logo" alt=""><h1>Changelog</h1>
-      <small>Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/NEWS.md" class="external-link"><code>NEWS.md</code></a></small>
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-    <div class="section level2">
-<h2 class="pkg-version" data-toc-text="development version" id="naniar-development-version">naniar (development version)<a class="anchor" aria-label="anchor" href="#naniar-development-version"></a></h2>
-</div>
-    <div class="section level2">
-<h2 class="pkg-version" data-toc-text="1.0.0" id="naniar-100">naniar 1.0.0<a class="anchor" aria-label="anchor" href="#naniar-100"></a></h2><p class="text-muted">CRAN release: 2023-02-02</p>
-<p>Version 1.0.0 of naniar is to signify that this release is associated with the publication of the associated JSS paper, <a href="doi:10.18637/jss.v105.i07" class="uri">doi:10.18637/jss.v105.i07</a>. There are also a few small changes that have been implemented in this release, which are described below.</p>
-<p>There is still a lot to do in naniar, and this release does not signify that there are no changes upcoming, more so to establish that this is a stable release, and that any changes upcoming will go through a more formal deprecation process and so on.</p>
-<div class="section level3">
-<h3 id="new-1-0-0">New<a class="anchor" aria-label="anchor" href="#new-1-0-0"></a></h3>
-<ul><li>The DOI in the CITATION is for a new JSS publication that will be registered after publication on CRAN.</li>
-<li>Replaced <code><a href="https://tidyr.tidyverse.org/reference/gather.html" class="external-link">tidyr::gather</a></code> with <code><a href="https://tidyr.tidyverse.org/reference/pivot_longer.html" class="external-link">tidyr::pivot_longer</a></code> - resolves <a href="https://github.com/njtierney/naniar/issues/301" class="external-link">#301</a></li>
-<li>added <code>set_n_miss</code> and <code>set_prop_miss</code> functions - resolved <a href="https://github.com/njtierney/naniar/issues/298" class="external-link">#298</a></li>
-</ul></div>
-<div class="section level3">
-<h3 id="bug-fixes-1-0-0">Bug Fixes<a class="anchor" aria-label="anchor" href="#bug-fixes-1-0-0"></a></h3>
-<ul><li>Fix bug in <code><a href="../reference/gg_miss_var.html">gg_miss_var()</a></code> where a warning appears to due change in how to remove legend <a href="https://github.com/njtierney/naniar/issues/288" class="external-link">#288</a>.</li>
-</ul></div>
-<div class="section level3">
-<h3 id="misc-1-0-0">Misc<a class="anchor" aria-label="anchor" href="#misc-1-0-0"></a></h3>
-<ul><li>Removed gdtools from naniar as no longer needed <a href="https://github.com/njtierney/naniar/issues/302" class="external-link">302</a>.</li>
-<li>added imports, <code>vctrs</code> and <code>cli</code> - which are both free dependencies as they are used within the already used tidyverse already.</li>
-</ul></div>
-</div>
-    <div class="section level2">
-<h2 class="pkg-version" data-toc-text="0.6.1" id="naniar-061-20210513-incandescent-lightbulbs-killed-the-arc-lamps">naniar 0.6.1 (2021/05/13) “Incandescent lightbulbs killed the Arc lamps”<a class="anchor" aria-label="anchor" href="#naniar-061-20210513-incandescent-lightbulbs-killed-the-arc-lamps"></a></h2><p class="text-muted">CRAN release: 2021-05-14</p>
-<div class="section level3">
-<h3 id="new-features-0-6-1">New features<a class="anchor" aria-label="anchor" href="#new-features-0-6-1"></a></h3>
-<ul><li>naniar now provides <code><a href="../reference/mcar_test.html">mcar_test()</a></code> for <a href="https://doi.org/10.1080/01621459.1988.10478722" class="external-link">Little’s (1988)</a> statistical test for missing completely at random (MCAR) data. The null hypothesis in this test is that the data is MCAR, and the test statistic is a chi-squared value. Given a high statistic value and low p-value, we can conclude data are not missing completely at random. Thanks to <a href="https://www.andrewheiss.com/" class="external-link">Andrew Heiss</a> for the <a href="https://github.com/njtierney/naniar/pull/279/" class="external-link">PR</a>.</li>
-<li>
-<code>common_na_strings</code> gains <code>"#N/A"</code>.</li>
-</ul></div>
-<div class="section level3">
-<h3 id="bug-fixes-0-6-1">Bug fixes<a class="anchor" aria-label="anchor" href="#bug-fixes-0-6-1"></a></h3>
-<ul><li>Fix bug in <code><a href="../reference/miss_var_span.html">miss_var_span()</a></code> (<a href="https://github.com/njtierney/naniar/issues/270" class="external-link">#270</a>) where the number of missings + number of complete values added up to more than the number of rows in the data. This was due to the remainder not being used when calculating the number of complete values.</li>
-<li>Fix bug in <code><a href="../reference/recode_shadow.html">recode_shadow()</a></code> (<a href="https://github.com/njtierney/naniar/issues/272" class="external-link">#272</a>) where adding the same special missing value in two subsequent operations fails.</li>
-</ul></div>
-</div>
-    <div class="section level2">
-<h2 class="pkg-version" data-toc-text="0.6.0" id="naniar-060-20200817-spur-of-the-lamp-post">naniar 0.6.0 (2020/08/17) “Spur of the lamp post”<a class="anchor" aria-label="anchor" href="#naniar-060-20200817-spur-of-the-lamp-post"></a></h2><p class="text-muted">CRAN release: 2020-09-02</p>
-<ul><li>Provide warning for <code>replace_with_na</code> when columns provided that don’t exist (see <a href="https://github.com/njtierney/naniar/issues/160" class="external-link">#160</a>). Thank you to <a href="https://github.com/michael-dewar" class="external-link">michael-dewar</a> for their help with this.</li>
-</ul><div class="section level3">
-<h3 id="breaking-changes-0-6-0">Breaking Changes<a class="anchor" aria-label="anchor" href="#breaking-changes-0-6-0"></a></h3>
-<ul><li>Drop the “nabular” and “shadow” classes (<a href="https://github.com/njtierney/naniar/issues/268" class="external-link">#268</a>) used in <code><a href="../reference/nabular.html">nabular()</a></code> and <code><a href="../reference/bind_shadow.html">bind_shadow()</a></code>. In doing so removes the functions, <code><a href="../reference/as_shadow.html">as_shadow()</a></code>, <code>is_shadow()</code>, <code>is_nabular()</code>, <code>new_nabular()</code>, <code>new_shadow()</code>. These were mostly used internally and it is not expected that users would have used this functions. If these were used, please file an issue and I can implement them again.</li>
-</ul></div>
-</div>
-    <div class="section level2">
-<h2 class="pkg-version" data-toc-text="0.5.2" id="naniar-052-20200628-silver-apple">naniar 0.5.2 (2020/06/28) “Silver Apple”<a class="anchor" aria-label="anchor" href="#naniar-052-20200628-silver-apple"></a></h2><p class="text-muted">CRAN release: 2020-06-29</p>
-<div class="section level3">
-<h3 id="minor-changes-0-5-2">Minor Changes<a class="anchor" aria-label="anchor" href="#minor-changes-0-5-2"></a></h3>
-<ul><li>Improvements to code in <code><a href="../reference/miss_var_summary.html">miss_var_summary()</a></code>, <code><a href="../reference/miss_var_table.html">miss_var_table()</a></code>, and <code><a href="../reference/prop-miss-complete-var.html">prop_miss_var()</a></code>, resulting in a 3-10x speedup.</li>
-</ul></div>
-</div>
-    <div class="section level2">
-<h2 class="pkg-version" data-toc-text="0.5.1" id="naniar-051-20200410-uncle-andrews-applewood-wardrobe">naniar 0.5.1 (2020/04/10) “Uncle Andrew’s Applewood Wardrobe”<a class="anchor" aria-label="anchor" href="#naniar-051-20200410-uncle-andrews-applewood-wardrobe"></a></h2><p class="text-muted">CRAN release: 2020-04-30</p>
-<div class="section level3">
-<h3 id="minor-changes-0-5-1">Minor Changes<a class="anchor" aria-label="anchor" href="#minor-changes-0-5-1"></a></h3>
-<ul><li>Fixes warnings and errors from <code>tibble</code> and subsequent downstream impacts on <code>simputation</code>.</li>
-</ul></div>
-</div>
-    <div class="section level2">
-<h2 class="pkg-version" data-toc-text="0.5.0" id="naniar-050-20200220-the-end-of-this-story-and-the-beginning-of-all-of-the-others">naniar 0.5.0 (2020/02/20) “The End of this Story and the Beginning of all of the Others”<a class="anchor" aria-label="anchor" href="#naniar-050-20200220-the-end-of-this-story-and-the-beginning-of-all-of-the-others"></a></h2><p class="text-muted">CRAN release: 2020-02-28</p>
-<div class="section level3">
-<h3 id="breaking-changes-0-5-0">Breaking Changes<a class="anchor" aria-label="anchor" href="#breaking-changes-0-5-0"></a></h3>
-<ul><li>The following functions related to calculating the proportion/percentage of missingness were made Defunct and will no longer work:
-<ul><li><code><a href="../reference/miss-pct-prop-defunct.html">miss_var_prop()</a></code></li>
-<li><code><a href="../reference/miss-pct-prop-defunct.html">complete_var_prop()</a></code></li>
-<li><code><a href="../reference/miss-pct-prop-defunct.html">miss_var_pct()</a></code></li>
-<li><code><a href="../reference/miss-pct-prop-defunct.html">complete_var_pct()</a></code></li>
-<li><code><a href="../reference/miss-pct-prop-defunct.html">miss_case_prop()</a></code></li>
-<li><code><a href="../reference/miss-pct-prop-defunct.html">complete_case_prop()</a></code></li>
-<li><code><a href="../reference/miss-pct-prop-defunct.html">miss_case_pct()</a></code></li>
-<li><code><a href="../reference/miss-pct-prop-defunct.html">complete_case_pct()</a></code></li>
-</ul></li>
-</ul><p>Instead use: <code><a href="../reference/prop-miss-complete-var.html">prop_miss_var()</a></code>, <code><a href="../reference/prop-miss-complete-var.html">prop_complete_var()</a></code>, <code><a href="../reference/pct-miss-complete-var.html">pct_miss_var()</a></code>, <code><a href="../reference/pct-miss-complete-var.html">pct_complete_var()</a></code>, <code><a href="../reference/prop-miss-complete-case.html">prop_miss_case()</a></code>, <code><a href="../reference/prop-miss-complete-case.html">prop_complete_case()</a></code>, <code><a href="../reference/pct-miss-complete-case.html">pct_miss_case()</a></code>, <code><a href="../reference/pct-miss-complete-case.html">pct_complete_case()</a></code>. (see <a href="https://github.com/njtierney/naniar/issues/242" class="external-link">242</a>)</p>
-<ul><li>
-<code><a href="../reference/replace_to_na.html">replace_to_na()</a></code> was made defunct, please use <code><a href="../reference/replace_with_na.html">replace_with_na()</a></code> instead. (see <a href="https://github.com/njtierney/naniar/issues/242" class="external-link">242</a>)</li>
-</ul></div>
-<div class="section level3">
-<h3 id="minor-changes-0-5-0">Minor changes<a class="anchor" aria-label="anchor" href="#minor-changes-0-5-0"></a></h3>
-<ul><li>
-<code>miss_var_cumsum</code> and <code>miss_case_cumsum</code> are now exported</li>
-<li>use <code>map_dfc</code> instead of <code>map_df</code>
-</li>
-<li>Fix various extra warnings and improve test coverage</li>
-</ul></div>
-<div class="section level3">
-<h3 id="bug-fixes-0-5-0">Bug Fixes<a class="anchor" aria-label="anchor" href="#bug-fixes-0-5-0"></a></h3>
-<ul><li>Address bug where the number of missings in a row is not calculated properly - see <a href="https://github.com/njtierney/naniar/issues/238" class="external-link">238</a> and <a href="https://github.com/njtierney/naniar/issues/232" class="external-link">232</a>. The solution involved using <code>rowSums(is.na(x))</code>, which was 3 times faster.</li>
-<li>Resolve bug in <code><a href="../reference/gg_miss_fct.html">gg_miss_fct()</a></code> where warning is given for non explicit NA values - see <a href="https://github.com/njtierney/naniar/issues/241" class="external-link">241</a>.</li>
-<li>skip vdiffr tests on github actions</li>
-<li>use <code><a href="https://tibble.tidyverse.org/reference/tibble.html" class="external-link">tibble()</a></code> not <code><a href="https://tibble.tidyverse.org/reference/deprecated.html" class="external-link">data_frame()</a></code>
-</li>
-</ul></div>
-</div>
-    <div class="section level2">
-<h2 class="pkg-version" data-toc-text="0.4.2" id="naniar-042-20190215-the-planting-of-the-tree">naniar 0.4.2 (2019/02/15) “The Planting of The Tree”<a class="anchor" aria-label="anchor" href="#naniar-042-20190215-the-planting-of-the-tree"></a></h2><p class="text-muted">CRAN release: 2019-02-15</p>
-<div class="section level3">
-<h3 id="improvements-0-4-2">Improvements<a class="anchor" aria-label="anchor" href="#improvements-0-4-2"></a></h3>
-<ul><li>The <code><a href="../reference/geom_miss_point.html">geom_miss_point()</a></code> <strong>ggplot2</strong> layer can now be converted into an interactive web-based version by the <code>ggplotly()</code> function in the <strong>plotly</strong> package. In order for this to work, <strong>naniar</strong> now exports the <code>geom2trace.GeomMissPoint()</code> function (users should never need to call <code>geom2trace.GeomMissPoint()</code> directly – <code>ggplotly()</code> calls it for you).</li>
-<li>adds <code>WORDLIST</code> for spelling thanks to <code><a href="https://usethis.r-lib.org/reference/use_spell_check.html" class="external-link">usethis::use_spell_check()</a></code>
-</li>
-<li>fix documentation <code>@seealso</code> bug (<a href="https://github.com/njtierney/naniar/issues/228" class="external-link">#228</a>) (<a href="https://github.com/sfirke" class="external-link">@sfirke</a>)</li>
-</ul></div>
-<div class="section level3">
-<h3 id="dependency-fixes-0-4-2">Dependency fixes<a class="anchor" aria-label="anchor" href="#dependency-fixes-0-4-2"></a></h3>
-<ul><li>
-<p>Thanks to a PR (<a href="https://github.com/njtierney/naniar/pull/223" class="external-link">#223</a>) from <a href="https://github.com/romainfrancois" class="external-link">@romainfrancois</a>:</p>
-<ul><li><p>This fixes two problems that were identified as part of reverse dependency checks of dplyr 0.8.0 release candidate. <a href="https://github.com/tidyverse/dplyr/blob/revdep_dplyr_0_8_0_RC/revdep/problems.md#naniar" class="external-link uri">https://github.com/tidyverse/dplyr/blob/revdep_dplyr_0_8_0_RC/revdep/problems.md#naniar</a></p></li>
-<li><p>n() must be imported or prefixed like any other function. In the PR, I’ve changed 1:n() to dplyr::row_number() as naniar seems to prefix all dplyr functions.</p></li>
-<li><p>update_shadow was only restoring the class attributes, changed so that it restores all attributes, this was causing problems when data was a grouped_df. This likely was a problem before too, but dplyr 0.8.0 is stricter about what is a grouped data frame.</p></li>
-</ul></li>
-</ul></div>
-</div>
-    <div class="section level2">
-<h2 class="pkg-version" data-toc-text="0.4.1" id="naniar-041-20181214">naniar 0.4.1 (2018/12/14)<a class="anchor" aria-label="anchor" href="#naniar-041-20181214"></a></h2><p class="text-muted">CRAN release: 2018-11-20</p>
-<div class="section level3">
-<h3 id="minor-changes-0-4-1">Minor Changes<a class="anchor" aria-label="anchor" href="#minor-changes-0-4-1"></a></h3>
-<ul><li>pkgdown updates: update favicon and logo, set up for gh-pages deployment</li>
-<li>use a scalar integer in <code>new_tibble</code>
-</li>
-</ul></div>
-</div>
-    <div class="section level2">
-<h2 class="pkg-version" data-toc-text="0.4.1" id="naniar-041-20181120-aslans-song">naniar 0.4.1 (2018/11/20) “Aslan’s Song”<a class="anchor" aria-label="anchor" href="#naniar-041-20181120-aslans-song"></a></h2><p class="text-muted">CRAN release: 2018-11-20</p>
-<div class="section level3">
-<h3 id="minor-change-0-4-1">Minor Change<a class="anchor" aria-label="anchor" href="#minor-change-0-4-1"></a></h3>
-<ul><li>Fixes to <code>new_tibble</code> <a href="https://github.com/njtierney/naniar/pull/220" class="external-link">#220</a> - Thanks to <a href="https://github.com/krlmlr" class="external-link">Kirill Müller</a>.</li>
-<li>Refactoring the capture of arguments from <code>rlang</code> <a href="https://github.com/njtierney/naniar/pull/218" class="external-link">#218</a> - thanks for <a href="https://github.com/lionel-" class="external-link">Lionel Henry</a>.</li>
-</ul></div>
-</div>
-    <div class="section level2">
-<h2 class="pkg-version" data-toc-text="0.4.0" id="naniar-040-20180910-an-unexpected-meeting">naniar 0.4.0 (2018/09/10) “An Unexpected Meeting”<a class="anchor" aria-label="anchor" href="#naniar-040-20180910-an-unexpected-meeting"></a></h2>
-<div class="section level3">
-<h3 id="new-feature-0-4-0">New Feature<a class="anchor" aria-label="anchor" href="#new-feature-0-4-0"></a></h3>
-<ul><li><p>Add custom label support for missings and not missings with functions <code>add_label_missings</code> and <code><a href="../reference/add_label_shadow.html">add_label_shadow()</a></code> and <code><a href="../reference/add_any_miss.html">add_any_miss()</a></code>. So you can now do `add_label_missings(data, missing = “custom_missing_label”, complete = “custom_complete_label”)</p></li>
-<li><p><code><a href="../reference/impute_median.html">impute_median()</a></code> and scoped variants</p></li>
-<li><p><code><a href="../reference/is_shade.html">any_shade()</a></code> returns a logical TRUE or FALSE depending on if there are any <code>shade</code> values</p></li>
-<li><p><code><a href="../reference/nabular.html">nabular()</a></code> an alias for <code><a href="../reference/bind_shadow.html">bind_shadow()</a></code> to tie the <code>nabular</code> term into the work.</p></li>
-<li><p><code>is_nabular()</code> checks if input is nabular.</p></li>
-<li><p><code><a href="../reference/geom_miss_point.html">geom_miss_point()</a></code> now gains the arguments from <code><a href="../reference/shadow_shift.html">shadow_shift()</a></code>/<code><a href="../reference/impute_below.html">impute_below()</a></code> for altering the amount of <code>jitter</code> and proportion below (<code>prop_below</code>).</p></li>
-<li><p>Added two new vignettes, “Exploring Imputed Values”, and “Special Missing Values”</p></li>
-<li><p><code>miss_var_summary</code> and <code>miss_case_summary</code> now no longer provide the cumulative sum of missingness in the summaries - this summary can be added back to the data with the option <code>add_cumsum = TRUE</code>. <a href="https://github.com/njtierney/naniar/issues/186" class="external-link">#186</a></p></li>
-<li>
-<p>Added <code>gg_miss_upset</code> to replace workflow of:</p>
-<pre><code><span><span class="va">data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> </span>
-<span>  <span class="fu"><a href="../reference/as_shadow_upset.html">as_shadow_upset</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu">UpSetR</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/UpSetR/man/upset.html" class="external-link">upset</a></span><span class="op">(</span><span class="op">)</span></span></code></pre>
-</li>
-</ul></div>
-<div class="section level3">
-<h3 id="major-change-0-4-0">Major Change<a class="anchor" aria-label="anchor" href="#major-change-0-4-0"></a></h3>
-<ul><li>
-<code>recode_shadow</code> now works! This function allows you to recode your missing values into special missing values. These special missing values are stored in the shadow part of the dataframe, which ends in <code>_NA</code>.</li>
-<li>implemented <code>shade</code> where appropriate throughout naniar, and also added verifiers, <code>is_shade</code>, <code>are_shade</code>, <code>which_are_shade</code>, and removed <code>which_are_shadow</code>.</li>
-<li>
-<code>as_shadow</code> and <code>bind_shadow</code> now return data of class <code>shadow</code>. This will feed into <code>recode_shadow</code> methods for flexibly adding new types of missing data.</li>
-<li>Note that in the future <code>shadow</code> might be changed to <code>nabble</code> or something similar.</li>
-</ul></div>
-<div class="section level3">
-<h3 id="minor-feature-0-4-0">Minor feature<a class="anchor" aria-label="anchor" href="#minor-feature-0-4-0"></a></h3>
-<ul><li>Functions <code><a href="../reference/add_label_shadow.html">add_label_shadow()</a></code> and <code><a href="../reference/add_label_missings.html">add_label_missings()</a></code> gain arguments so you can only label according to the missingness / shadowy-ness of given variables.</li>
-<li>new function <code>which_are_shadow()</code>, to tell you which values are shadows.</li>
-<li>new function <code>long_shadow()</code>, which converts data in shadow/nabular form into a long format suitable for plotting. Related to <a href="https://github.com/njtierney/naniar/issues/165" class="external-link">#165</a>
-</li>
-<li>Added tests for <code>miss_scan_count</code>
-</li>
-</ul></div>
-<div class="section level3">
-<h3 id="minor-changes-0-4-0">Minor Changes<a class="anchor" aria-label="anchor" href="#minor-changes-0-4-0"></a></h3>
-<ul><li>
-<code>gg_miss_upset</code> gets a better default presentation by ordering by the largest intersections, and also an improved error message when data with only 1 or no variables have missing values.</li>
-<li>
-<code>shadow_shift</code> gains a more informative error message when it doesn’t know the class.</li>
-<li>Changed <code>common_na_string</code> to include escape characters for “?”, “<em>”, ”.” so that if they are used in replacement or searching functions they don’t return the wildcard results from the characters ”?”, ”</em>”, and “.”.</li>
-<li>
-<code>miss_case_table</code> and <code>miss_var_table</code> now has final column names <code>pct_vars</code>, and <code>pct_cases</code> instead of <code>pct_miss</code> - fixes <a href="https://github.com/njtierney/naniar/issues/178" class="external-link">#178</a>.</li>
-</ul></div>
-<div class="section level3">
-<h3 id="breaking-changes-0-4-0">Breaking Changes<a class="anchor" aria-label="anchor" href="#breaking-changes-0-4-0"></a></h3>
-<ul><li>Deprecated old names of the scalar missingness summaries, in favour of a more consistent syntax <a href="https://github.com/njtierney/naniar/issues/171" class="external-link">#171</a>. The old the and new are:</li>
-</ul><table class="table"><thead><tr class="header"><th align="left">old_names</th>
-<th align="left">new_names</th>
-</tr></thead><tbody><tr class="odd"><td align="left"><code>miss_case_pct</code></td>
-<td align="left"><code>pct_miss_case</code></td>
-</tr><tr class="even"><td align="left"><code>miss_case_prop</code></td>
-<td align="left"><code>prop_miss_case</code></td>
-</tr><tr class="odd"><td align="left"><code>miss_var_pct</code></td>
-<td align="left"><code>pct_miss_var</code></td>
-</tr><tr class="even"><td align="left"><code>miss_var_prop</code></td>
-<td align="left"><code>prop_miss_var</code></td>
-</tr><tr class="odd"><td align="left"><code>complete_case_pct</code></td>
-<td align="left"><code>pct_complete_case</code></td>
-</tr><tr class="even"><td align="left"><code>complete_case_prop</code></td>
-<td align="left"><code>prop_complete_case</code></td>
-</tr><tr class="odd"><td align="left"><code>complete_var_pct</code></td>
-<td align="left"><code>pct_complete_var</code></td>
-</tr><tr class="even"><td align="left"><code>complete_var_prop</code></td>
-<td align="left"><code>prop_complete_var</code></td>
-</tr></tbody></table><p>These old names will be made defunct in 0.5.0, and removed completely in 0.6.0.</p>
-<ul><li>
-<code>impute_below</code> has changed to be an alias of <code>shadow_shift</code> - that is it operates on a single vector. <code>impute_below_all</code> operates on all columns in a dataframe (as specified in <a href="https://github.com/njtierney/naniar/issues/159" class="external-link">#159</a>)</li>
-</ul></div>
-<div class="section level3">
-<h3 id="bug-fix-0-4-0">Bug fix<a class="anchor" aria-label="anchor" href="#bug-fix-0-4-0"></a></h3>
-<ul><li>Ensured that <code>miss_scan_count</code> actually <code>return</code>’d something.</li>
-<li>
-<code>gg_miss_var(airquality)</code> now prints the ggplot - a typo meant that this did not print the plot</li>
-</ul></div>
-</div>
-    <div class="section level2">
-<h2 class="pkg-version" data-toc-text="0.3.1" id="naniar-031-20180610-strawberrys-adventure">naniar 0.3.1 (2018/06/10) “Strawberry’s Adventure”<a class="anchor" aria-label="anchor" href="#naniar-031-20180610-strawberrys-adventure"></a></h2><p class="text-muted">CRAN release: 2018-06-08</p>
-<div class="section level3">
-<h3 id="minor-change-0-3-1">Minor Change<a class="anchor" aria-label="anchor" href="#minor-change-0-3-1"></a></h3>
-<p>This is a patch release that removes <code>tidyselect</code> from the package Imports, as it is unnecessary. Fixes <a href="https://github.com/njtierney/naniar/issues/174" class="external-link">#174</a></p>
-</div>
-</div>
-    <div class="section level2">
-<h2 class="pkg-version" data-toc-text="0.3.0" id="id_-naniar-030-20180606-digory-and-his-uncle-are-both-in-trouble"># naniar 0.3.0 (2018/06/06) “Digory and his Uncle Are Both in Trouble”<a class="anchor" aria-label="anchor" href="#id_-naniar-030-20180606-digory-and-his-uncle-are-both-in-trouble"></a></h2><p class="text-muted">CRAN release: 2018-06-07</p>
-<div class="section level3">
-<h3 id="new-features-0-3-0">New Features<a class="anchor" aria-label="anchor" href="#new-features-0-3-0"></a></h3>
-<ul><li><p>Added <code><a href="../reference/all-is-miss-complete.html">all_miss()</a></code> / <code><a href="../reference/all-is-miss-complete.html">all_na()</a></code> equivalent to <code>all(is.na(x))</code></p></li>
-<li><p>Added <code><a href="../reference/any-na.html">any_complete()</a></code> equivalent to <code>all(complete.cases(x))</code></p></li>
-<li><p>Added <code><a href="../reference/any-na.html">any_miss()</a></code> equivalent to <code>anyNA(x)</code></p></li>
-<li><p>Added <code>common_na_numbers</code> and finalised <code>common_na_strings</code> - to provide a list of commonly used NA values <a href="https://github.com/njtierney/naniar/issues/168" class="external-link">#168</a></p></li>
-<li><p>Added <code>miss_var_which</code>, to lists the variable names with missings</p></li>
-<li>
-<p>Added <code>as_shadow_upset</code> which gets the data into a format suitable for plotting as an <code>UpSetR</code> plot:</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/as_shadow_upset.html">as_shadow_upset</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu">UpSetR</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/UpSetR/man/upset.html" class="external-link">upset</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-</li>
-<li>
-<p>Added some imputation functions to assist with exploring missingness structure and visualisation:</p>
-<ul><li>
-<code>impute_below</code> Perfoms as for <code>shadow_shift</code>, but performs on all columns. This means that it imputes missing values 10% below the range of the data (powered by <code>shadow_shift</code>), to facilitate graphical exloration of the data. Closes <a href="https://github.com/njtierney/naniar/issues/145" class="external-link">#145</a> There are also scoped variants that work for specific named columns: <code>impute_below_at</code>, and for columns that satisfy some predicate function: <code>impute_below_if</code>.</li>
-<li>
-<code>impute_mean</code>, imputes the mean value, and scoped variants <code>impute_mean_at</code>, and <code>impute_mean_if</code>.</li>
-</ul></li>
-<li><p><code>impute_below</code> and <code>shadow_shift</code> gain arguments <code>prop_below</code> and <code>jitter</code> to control the degree of shift, and also the extent of jitter.</p></li>
-<li><p>Added <code>complete_{case/var}_{pct/prop}</code>, which complement <code>miss_{var/case}_{pct/prop}</code> <a href="https://github.com/njtierney/naniar/issues/150" class="external-link">#150</a></p></li>
-<li><p>Added <code>unbind_shadow</code> and <code>unbind_data</code> as helpers to remove shadow columns from data, and data from shadows, respectively.</p></li>
-<li><p>Added <code>is_shadow</code> and <code>are_shadow</code> to determine if something contains a shadow column. simimlar to <code><a href="https://rlang.r-lib.org/reference/are_na.html" class="external-link">rlang::is_na</a></code> and <code>rland::are_na</code>, <code>is_shadow</code> this returns a logical vector of length 1, and <code>are_shadow</code> returns a logical vector of length of the number of names of a data.frame. This might be revisited at a later point (see <code>any_shade</code> in <code>add_label_shadow</code>).</p></li>
-<li><p>Aesthetics now map as expected in geom_miss_point(). This means you can write things like <code>geom_miss_point(aes(colour = Month))</code> and it works appropriately. Fixed by <a href="https://github.com/seasmith" class="external-link">Luke Smith</a> in Pull request <a href="https://github.com/njtierney/naniar/pull/144" class="external-link">#144</a>, fixing <a href="https://github.com/njtierney/naniar/issues/137" class="external-link">#137</a>.</p></li>
-</ul></div>
-<div class="section level3">
-<h3 id="minor-changes-0-3-0">Minor Changes<a class="anchor" aria-label="anchor" href="#minor-changes-0-3-0"></a></h3>
-<ul><li><p><code>miss_var_summary</code> and <code>miss_case_summary</code> now return use <code>order = TRUE</code> by default, so cases and variables with the most missings are presented in descending order. Fixes <a href="https://github.com/njtierney/naniar/issues/163" class="external-link">#163</a></p></li>
-<li>
-<p>Changes for Visualisation:</p>
-<ul><li>Changed the default colours used in <code>gg_miss_case</code> and <code>gg_miss_var</code> to lorikeet purple (from ochRe package: <a href="https://github.com/ropenscilabs/ochRe" class="external-link uri">https://github.com/ropenscilabs/ochRe</a>)</li>
-<li>
-<code>gg_miss_case</code>
-<ul><li>The y axis label is now …</li>
-<li>Default presentation is with <code>order_cases = TRUE</code>.</li>
-<li>Gains a <code>show_pct</code> option to be consistent with <code>gg_miss_var</code> <a href="https://github.com/njtierney/naniar/issues/153" class="external-link">#153</a>
-</li>
-</ul></li>
-<li>
-<code>gg_miss_which</code> is rotated 90 degrees so it is easier to read variable names</li>
-<li>
-<code>gg_miss_fct</code> uses a minimal theme and tilts the axis labels <a href="https://github.com/njtierney/naniar/issues/118" class="external-link">#118</a>.</li>
-</ul></li>
-<li><p>imported <code>is_na</code> and <code>are_na</code> from <code>rlang</code>.</p></li>
-<li><p>Added <code>common_na_strings</code>, a list of common <code>NA</code> values <a href="https://github.com/njtierney/naniar/issues/168" class="external-link">#168</a>.</p></li>
-<li><p>Added some detail on alternative methods for replacing with NA in the vignette “replacing values with NA”.</p></li>
-</ul></div>
-</div>
-    <div class="section level2">
-<h2 class="pkg-version" data-toc-text="0.2.0" id="id_-naniar-020-20180208-the-first-joke-and-other-matters"># naniar 0.2.0 (2018/02/08) (“The First Joke and Other Matters”)<a class="anchor" aria-label="anchor" href="#id_-naniar-020-20180208-the-first-joke-and-other-matters"></a></h2><p class="text-muted">CRAN release: 2018-02-09</p>
-<div class="section level3">
-<h3 id="new-features-0-2-0">New Features<a class="anchor" aria-label="anchor" href="#new-features-0-2-0"></a></h3>
-<ul><li><p>Speed improvements. Thanks to the help, contributions, and discussion with Romain François and Jim Hester, naniar now has greatly improved speed for calculating the missingness in each row. These speedups should continue to improve in future releases.</p></li>
-<li>
-<p>New “scoped variants” of <code>replace_with_na</code>, thankyou to Colin Fay for his work on this:</p>
-<ul><li>
-<code>replace_with_na_all</code> replaces all NAs across the dataframe that meet a specified condition (using the syntax <code>~.x == -99</code>)</li>
-<li>
-<code>replace_with_na_at</code> replaces all NAs across for specified variables</li>
-<li>
-<code>replace_with_na_if</code> replaces all NAs for those variables that satisfy some predicate function (e.g., is.character)</li>
-</ul></li>
-<li><p>added <code>which_na</code> - replacement for <code>which(is.na(x))</code></p></li>
-<li><p><code>miss_scan_count</code>. This makes it easier for users to search for particular occurrences of these values across their variables. <a href="https://github.com/njtierney/naniar/issues/119" class="external-link">#119</a></p></li>
-<li><p><code>n_miss_row</code> calculates the number of missing values in each row, returning a vector. There are also 3 other functions which are similar in spirit: <code>n_complete_row</code>, <code>prop_miss_row</code>, and <code>prop_complete_row</code>, which return a vector of the number of complete obserations, the proportion of missings in a row, and the proportion of complete obserations in a row</p></li>
-<li><p><code>add_miss_cluster</code> is a new function that calculates a cluster of missingness for each row, using <code>hclust</code>. This can be useful in exploratory modelling of missingness, similar to Tierney et al 2015: “doi: 10.1136/bmjopen-2014-007450” and Barnett et al. 2017: “doi: 10.1136/bmjopen-2017-017284”</p></li>
-<li><p>Now exported <code>where_na</code> - a function that returns the positions of NA values. For a dataframe it returns a matrix of row and col positions of NAs, and for a vector it returns a vector of positions of NAs. (<a href="https://github.com/njtierney/naniar/issues/105" class="external-link">#105</a>)</p></li>
-</ul></div>
-<div class="section level3">
-<h3 id="minor-changes-0-2-0">Minor changes<a class="anchor" aria-label="anchor" href="#minor-changes-0-2-0"></a></h3>
-<ul><li>Updated the vignette “Gallery of Missing Data Visualisations” to include the <code>facet</code> features and <code>order_cases</code>.</li>
-<li>
-<code>bind_shadow</code> gains a <code>only_miss</code> argument. When set to FALSE (the default) it will bind a dataframe with all of the variables duplicated with their shadow. Setting this to TRUE will bind variables only those variables that contain missing values.</li>
-<li>Cleaned up the visualisation of <code>gg_miss_case</code> to be clearer and less cluttered ( <a href="https://github.com/njtierney/naniar/issues/117" class="external-link">#117</a>), also added n <code>order_cases</code> option to order by cases.</li>
-<li>Added a <code>facet</code> argument to <code>gg_miss_var</code>, <code>gg_miss_case</code>, and <code>gg_miss_span</code>. This makes it easier for users to visualise these plots across the values of another variable. In the future I will consider adding <code>facet</code> to the other shorthand plotting function, but at the moment these seemed to be the ones that would benefit the most from this feature.</li>
-</ul></div>
-<div class="section level3">
-<h3 id="bug-fix-0-2-0">Bug fix<a class="anchor" aria-label="anchor" href="#bug-fix-0-2-0"></a></h3>
-<ul><li>
-<code>oceanbuoys</code> now is numeric type for year, latitude, and longitude, previously it was factor. <a href="https://github.com/njtierney/naniar/issues/110" class="external-link">See related issue</a>
-</li>
-<li>Improved handling of <code>shadow_shift</code> when there are Inf or -Inf values (see <a href="https://github.com/njtierney/naniar/issues/90" class="external-link">#117</a>)</li>
-</ul></div>
-<div class="section level3">
-<h3 id="breaking-change-0-2-0">Breaking change<a class="anchor" aria-label="anchor" href="#breaking-change-0-2-0"></a></h3>
-<ul><li><p>Deprecated <code>replace_to_na</code>, with <code>replace_with_na</code>, as it is a more natural phrase (“replace coffee to tea” vs “replace coffee with tea”). This will be made defunct in the next version.</p></li>
-<li><p><code>cast_shadow</code> no longer works when called as <code>cast_shadow(data)</code>. This action used to return all variables, and then shadow variables for the variables that only contained missing values. This was inconsistent with the use of <code>cast_shadow(data, var1, var2)</code>. A new option has been added to <code>bind_shadow</code> that controls this - discussed below. See more details at <a href="https://github.com/njtierney/naniar/issues/106" class="external-link">issue 65</a>.</p></li>
-<li><p>Change behaviour of <code>cast_shadow</code> so that the default option is to return only the variables that contain missings. This is different to <code>bind_shadow</code>, which binds a complete shadow matrix to the dataframe. A way to think about this is that the shadow is only cast on variables that contain missing values, whereas a bind is binding a complete shadow to the data. This may change in the future to be the default option for <code>bind_shadow</code>.</p></li>
-</ul></div>
-<div class="section level3">
-<h3 id="minor-changes-0-2-0-1">Minor Changes<a class="anchor" aria-label="anchor" href="#minor-changes-0-2-0-1"></a></h3>
-<ul><li>Update vignettes to have floating menu and better figure size.</li>
-<li>minor changes to graphics in gg_miss_fct - change legend title from “Percent Missing” to “% Miss”.</li>
-</ul></div>
-</div>
-    <div class="section level2">
-<h2 class="pkg-version" data-toc-text="0.1.0" id="id_-naniar-010-20170809-the-founding-of-naniar"># naniar 0.1.0 (2017/08/09) “The Founding of <code>naniar</code>”<a class="anchor" aria-label="anchor" href="#id_-naniar-010-20170809-the-founding-of-naniar"></a></h2><p class="text-muted">CRAN release: 2017-08-09</p>
-<ul><li>This is the first release of <code>naniar</code> onto CRAN, updates to <code>naniar</code> will happen reasonably regularly after this approximately every 1-2 months</li>
-</ul></div>
-    <div class="section level2">
-<h2 class="pkg-version" data-toc-text="0.0.9.9995" id="id_-naniar-0099995-20170807"># naniar 0.0.9.9995 (2017/08/07)<a class="anchor" aria-label="anchor" href="#id_-naniar-0099995-20170807"></a></h2>
-<div class="section level3">
-<h3 id="name-change-0-0-9-9995">Name change<a class="anchor" aria-label="anchor" href="#name-change-0-0-9-9995"></a></h3>
-<ul><li>After careful consideration, I have changed back to <code>naniar</code>
-</li>
-</ul></div>
-<div class="section level3">
-<h3 id="major-change-0-0-9-9995">Major Change<a class="anchor" aria-label="anchor" href="#major-change-0-0-9-9995"></a></h3>
-<ul><li>three new functions : <code>miss_case_cumsum</code> / <code>miss_var_cumsum</code> / <code>replace_to_na</code>
-</li>
-<li>two new visualisations : <code>gg_var_cumsum</code> &amp; <code>gg_case_cumsum</code>
-</li>
-</ul></div>
-<div class="section level3">
-<h3 id="new-feature-0-0-9-9995">New Feature<a class="anchor" aria-label="anchor" href="#new-feature-0-0-9-9995"></a></h3>
-<ul><li>
-<code>group_by</code> is now respected by the following functions:
-<ul><li><code><a href="../reference/miss_case_cumsum.html">miss_case_cumsum()</a></code></li>
-<li><code><a href="../reference/miss_case_summary.html">miss_case_summary()</a></code></li>
-<li><code><a href="../reference/miss_case_table.html">miss_case_table()</a></code></li>
-<li><code><a href="../reference/miss_prop_summary.html">miss_prop_summary()</a></code></li>
-<li><code><a href="../reference/miss_var_cumsum.html">miss_var_cumsum()</a></code></li>
-<li><code><a href="../reference/miss_var_run.html">miss_var_run()</a></code></li>
-<li><code><a href="../reference/miss_var_span.html">miss_var_span()</a></code></li>
-<li><code><a href="../reference/miss_var_summary.html">miss_var_summary()</a></code></li>
-<li><code><a href="../reference/miss_var_table.html">miss_var_table()</a></code></li>
-</ul></li>
-</ul></div>
-<div class="section level3">
-<h3 id="minor-changes-0-0-9-9995">Minor changes<a class="anchor" aria-label="anchor" href="#minor-changes-0-0-9-9995"></a></h3>
-<ul><li>Reviewed documentation for all functions and improved wording, grammar, and style.</li>
-<li>Converted roxygen to roxygen markdown</li>
-<li>updated vignettes and readme</li>
-<li>added a new vignette “naniar-visualisation”, to give a quick overview of the visualisations provided with naniar.</li>
-<li>changed <code>label_missing*</code> to <code>label_miss</code> to be more consistent with the rest of naniar</li>
-<li>Add <code>pct</code> and <code>prop</code> helpers (<a href="https://github.com/njtierney/naniar/issues/78" class="external-link">#78</a>)</li>
-<li>removed <code>miss_df_pct</code> - this was literally the same as <code>pct_miss</code> or <code>prop_miss</code>.</li>
-<li>break larger files into smaller, more manageable files (<a href="https://github.com/njtierney/naniar/issues/83" class="external-link">#83</a>)</li>
-<li>
-<code>gg_miss_var</code> gets a <code>show_pct</code> argument to show the percentage of missing values (Thanks <a href="https://github.com/jenniferthompson" class="external-link">Jennifer</a> for the helpful feedback! :))</li>
-</ul></div>
-<div class="section level3">
-<h3 id="minor-changes-0-0-9-9995-1">Minor changes<a class="anchor" aria-label="anchor" href="#minor-changes-0-0-9-9995-1"></a></h3>
-<ul><li>
-<code>miss_var_summary</code> &amp; <code>miss_case_summary</code> now have consistent output (one was ordered by n_missing, not the other).</li>
-<li>prevent error in <code>miss_case_pct</code>
-</li>
-<li>
-<code>enquo_x</code> is now <code>x</code>
-</li>
-<li>Now has ByteCompile to TRUE</li>
-<li>add Colin to auth</li>
-</ul></div>
-</div>
-    <div class="section level2">
-<h2 class="pkg-version" data-toc-text="0.0.6.9100" id="id_-naniar-0069100-20170321"># naniar 0.0.6.9100 (2017/03/21)<a class="anchor" aria-label="anchor" href="#id_-naniar-0069100-20170321"></a></h2>
-<ul><li>Added <code>prop_miss</code> and the complement <code>prop_complete</code>. Where <code>n_miss</code> returns the number of missing values, <code>prop_miss</code> returns the proportion of missing values. Likewise, <code>prop_complete</code> returns the proportion of complete values.</li>
-</ul><div class="section level3">
-<h3 id="defunct-functions-0-0-6-9100">Defunct functions<a class="anchor" aria-label="anchor" href="#defunct-functions-0-0-6-9100"></a></h3>
-<ul><li>As stated in 0.0.5.9000, to address <a href="https://github.com/njtierney/naniar/issues/38" class="external-link">Issue </a><a href="https://github.com/njtierney/naniar/issues/38" class="external-link">#38</a>, I am moving towards the format miss_type_value/fun, because it makes more sense to me when tabbing through functions.</li>
-</ul><p>The left hand side functions have been made defunct in favour of the right hand side. - <code>percent_missing_case()</code> –&gt; <code><a href="../reference/miss-pct-prop-defunct.html">miss_case_pct()</a></code> - <code>percent_missing_var()</code> –&gt; <code><a href="../reference/miss-pct-prop-defunct.html">miss_var_pct()</a></code> - <code>percent_missing_df()</code> –&gt; <code>miss_df_pct()</code> - <code>summary_missing_case()</code> –&gt; <code><a href="../reference/miss_case_summary.html">miss_case_summary()</a></code> - <code>summary_missing_var()</code> –&gt; <code><a href="../reference/miss_var_summary.html">miss_var_summary()</a></code> - <code>table_missing_case()</code> –&gt; <code><a href="../reference/miss_case_table.html">miss_case_table()</a></code> - <code>table_missing_var()</code> –&gt; <code><a href="../reference/miss_var_table.html">miss_var_table()</a></code></p>
-</div>
-</div>
-    <div class="section level2">
-<h2 class="pkg-version" data-toc-text="0.0.5.9000" id="id_-naniar-0059000-20160108"># naniar 0.0.5.9000 (2016/01/08)<a class="anchor" aria-label="anchor" href="#id_-naniar-0059000-20160108"></a></h2>
-<div class="section level3">
-<h3 id="deprecated-functions-0-0-5-9000">Deprecated functions<a class="anchor" aria-label="anchor" href="#deprecated-functions-0-0-5-9000"></a></h3>
-<ul><li>To address <a href="https://github.com/njtierney/naniar/issues/38" class="external-link">Issue </a><a href="https://github.com/njtierney/naniar/issues/38" class="external-link">#38</a>, I am moving towards the format miss_type_value/fun, because it makes more sense to me when tabbing through functions.</li>
-<li>
-<code>miss_*</code> = I want to explore missing values</li>
-<li>
-<code>miss_case_*</code> = I want to explore missing cases</li>
-<li>
-<code>miss_case_pct</code> = I want to find the percentage of cases containing a missing value</li>
-<li>
-<code>miss_case_summary</code> = I want to find the number / percentage of missings in each case</li>
-<li>
-<code>miss_case_table</code> = I want a tabulation of the number / percentage of cases missing</li>
-</ul><p>This is more consistent and easier to reason with.</p>
-<p>Thus, I have renamed the following functions: - <code>percent_missing_case()</code> –&gt; <code><a href="../reference/miss-pct-prop-defunct.html">miss_case_pct()</a></code> - <code>percent_missing_var()</code> –&gt; <code><a href="../reference/miss-pct-prop-defunct.html">miss_var_pct()</a></code> - <code>percent_missing_df()</code> –&gt; <code>miss_df_pct()</code> - <code>summary_missing_case()</code> –&gt; <code><a href="../reference/miss_case_summary.html">miss_case_summary()</a></code> - <code>summary_missing_var()</code> –&gt; <code><a href="../reference/miss_var_summary.html">miss_var_summary()</a></code> - <code>table_missing_case()</code> –&gt; <code><a href="../reference/miss_case_table.html">miss_case_table()</a></code> - <code>table_missing_var()</code> –&gt; <code><a href="../reference/miss_var_table.html">miss_var_table()</a></code></p>
-<p>These will be made defunct in the next release, 0.0.6.9000 (“The Wood Between Worlds”).</p>
-</div>
-</div>
-    <div class="section level2">
-<h2 class="pkg-version" data-toc-text="0.0.4.9000" id="id_-naniar-0049000-20161231"># naniar 0.0.4.9000 (2016/12/31)<a class="anchor" aria-label="anchor" href="#id_-naniar-0049000-20161231"></a></h2>
-<div class="section level3">
-<h3 id="new-features-0-0-4-9000">New features<a class="anchor" aria-label="anchor" href="#new-features-0-0-4-9000"></a></h3>
-<ul><li>
-<code>n_complete</code> is a complement to <code>n_miss</code>, and counts the number of complete values in a vector, matrix, or dataframe.</li>
-</ul></div>
-<div class="section level3">
-<h3 id="bug-fixes-0-0-4-9000">Bug fixes<a class="anchor" aria-label="anchor" href="#bug-fixes-0-0-4-9000"></a></h3>
-<ul><li>
-<code>shadow_shift</code> now handles cases where there is only 1 complete value in a vector.</li>
-</ul></div>
-<div class="section level3">
-<h3 id="other-changes-0-0-4-9000">Other changes<a class="anchor" aria-label="anchor" href="#other-changes-0-0-4-9000"></a></h3>
-<ul><li>added much more comprehensive testing with <code>testthat</code>.</li>
-</ul></div>
-</div>
-    <div class="section level2">
-<h2 class="pkg-version" data-toc-text="0.0.3.9901" id="id_-naniar-0039901-20161218"># naniar 0.0.3.9901 (2016/12/18)<a class="anchor" aria-label="anchor" href="#id_-naniar-0039901-20161218"></a></h2>
-<p>After a burst of effort on this package I have done some refactoring and thought hard about where this package is going to go. This meant that I had to make the decision to rename the package from ggmissing to naniar. The name may strike you as strange but it reflects the fact that there are many changes happening, and that we will be working on creating a nice utopia (like Narnia by CS Lewis) that helps us make it easier to work with missing data</p>
-<div class="section level3">
-<h3 id="new-features-under-development-0-0-3-9901">New Features (under development)<a class="anchor" aria-label="anchor" href="#new-features-under-development-0-0-3-9901"></a></h3>
-<ul><li><p><code>add_n_miss</code> and <code>add_prop_miss</code> are helpers that add columns to a dataframe containing the number and proportion of missing values. An example has been provided to use decision trees to explore missing data structure as in “doi: 10.1136/bmjopen-2014-007450”</p></li>
-<li><p><code><a href="../reference/geom_miss_point.html">geom_miss_point()</a></code> now supports transparency, thanks to <a href="https://github.com/seasmith" class="external-link">@seasmith</a> (Luke Smith)</p></li>
-<li><p>more shadows. These are mainly around <code>bind_shadow</code> and <code>gather_shadow</code>, which are helper functions to assist with creating</p></li>
-</ul></div>
-<div class="section level3">
-<h3 id="bug-fixes-0-0-3-9901">Bug fixes<a class="anchor" aria-label="anchor" href="#bug-fixes-0-0-3-9901"></a></h3>
-<ul><li><p><code>geom_missing_point()</code> broke after the new release of ggplot2 2.2.0, but this is now fixed by ensuring that it inherits from GeomPoint, rather than just a new Geom. Thanks to Mitchell O’hara-Wild for his help with this.</p></li>
-<li><p>missing data summaries <code>table_missing_var</code> and <code>table_missing_case</code> also now return more sensible numbers and variable names. It is possible these function names will change in the future, as these are kind of verbose.</p></li>
-<li><p>semantic versioning was incorrectly entered in the DESCRIPTION file as 0.2.9000, so I changed it to 0.0.2.9000, and then to 0.0.3.9000 now to indicate the new changes, hopefully this won’t come back to bite me later. I think I accidentally did this with visdat at some point as well. Live and learn.</p></li>
-</ul></div>
-<div class="section level3">
-<h3 id="other-changes-0-0-3-9901">Other changes<a class="anchor" aria-label="anchor" href="#other-changes-0-0-3-9901"></a></h3>
-<ul><li><p>gathered related functions into single R files rather than leaving them in their own.</p></li>
-<li><p>correctly imported the <code>%&gt;%</code> operator from magrittr, and removed a lot of chaff around <code>@importFrom</code> - really don’t need to use <code>@importFrom</code> that often.</p></li>
-</ul></div>
-</div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
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-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
-</div>
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-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
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-            return `${s.dir} >	<div class="search-details"> ${s.title}</div>`;
-          } else if (s.previous_headings == "") {
-            return `${s.dir} >	<div class="search-details"> ${s.title}</div> > ${s.what}`;
-          } else {
-            return `${s.dir} >	<div class="search-details"> ${s.title}</div> > ${s.previous_headings} > ${s.what}`;
-          }
-        },
-      },
-    },
-  ]).on('autocomplete:selected', function(event, s) {
-    window.location.href = s.path + "?q=" + q + "#" + s.id;
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-})(window.jQuery || window.$)
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diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
deleted file mode 100644
index 6adfad70..00000000
--- a/docs/pkgdown.yml
+++ /dev/null
@@ -1,14 +0,0 @@
-pandoc: 2.19.2
-pkgdown: 2.0.7
-pkgdown_sha: ~
-articles:
-  exploring-imputed-values: exploring-imputed-values.html
-  getting-started-w-naniar: getting-started-w-naniar.html
-  naniar-visualisation: naniar-visualisation.html
-  replace-with-na: replace-with-na.html
-  special-missing-values: special-missing-values.html
-last_built: 2023-05-01T23:09Z
-urls:
-  reference: http://naniar.njtierney.com/reference
-  article: http://naniar.njtierney.com/articles
-
diff --git a/docs/pull_request_template.html b/docs/pull_request_template.html
deleted file mode 100644
index 28a96ce1..00000000
--- a/docs/pull_request_template.html
+++ /dev/null
@@ -1,107 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>NA • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png"><script src="deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="pkgdown.js"></script><meta property="og:title" content="NA"><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-<![endif]--></head><body>
-    <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
-    
-
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-primary"><div class="container">
-    
-    <a class="navbar-brand me-2" href="index.html">naniar</a>
-
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0.9000</small>
-
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-    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
-      <span class="navbar-toggler-icon"></span>
-    </button>
-
-    <div id="navbar" class="collapse navbar-collapse ms-3">
-      <ul class="navbar-nav me-auto"><li class="nav-item">
-  <a class="nav-link" href="articles/getting-started-w-naniar.html">Getting Started</a>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="articles/naniar-visualisation.html">Gallery</a>
-</li>
-<li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown-articles">Articles</a>
-  <div class="dropdown-menu" aria-labelledby="dropdown-articles">
-    <a class="dropdown-item" href="articles/replace-with-na.html">Replace with NA</a>
-    <a class="dropdown-item" href="articles/special-missing-values.html">Special Missings</a>
-    <a class="dropdown-item" href="articles/exploring-imputed-values.html">Exploring Imputations</a>
-  </div>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="reference/index.html">Reference</a>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="news/index.html">News</a>
-</li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
-  <a class="external-link nav-link" href="https://github.com/njtierney/naniar/" aria-label="github">
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-     
-  </a>
-</li>
-      </ul></div>
-
-    
-  </div>
-</nav><div class="container template-title-body">
-<div class="row">
-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="logo.png" class="logo" alt=""><h1>NA</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/.github/pull_request_template.md" class="external-link"><code>.github/pull_request_template.md</code></a></small>
-    </div>
-
-
-<div class="section level2">
-<h2 id="description">Description<a class="anchor" aria-label="anchor" href="#description"></a></h2>
-<!--- Describe your changes in detail -->
-</div>
-<div class="section level2">
-<h2 id="related-issue">Related Issue<a class="anchor" aria-label="anchor" href="#related-issue"></a></h2>
-<!--- if this closes an issue make sure include e.g., "fix #4"
-or similar - or if just relates to an issue make sure to mention
-it like "#4" -->
-</div>
-<div class="section level2">
-<h2 id="example">Example<a class="anchor" aria-label="anchor" href="#example"></a></h2>
-<!--- if introducing a new feature or changing behavior of existing
-methods/functions, include an example if possible to do in brief form -->
-</div>
-<div class="section level2">
-<h2 id="tests">Tests<a class="anchor" aria-label="anchor" href="#tests"></a></h2>
-<!--- Did you remember to include tests? Unless you're just changing
-grammar, please include new tests for your change -->
-</div>
-<div class="section level2">
-<h2 id="news--description">NEWS + DESCRIPTION<a class="anchor" aria-label="anchor" href="#news--description"></a></h2>
-<!--- If you added a new feature or changed behaviour, describe the new/changed behaviour in the NEWS.md file. If it is a new feature, please bump the version in the DESCRIPTION and NEWS.md files  -->
-</div>
-
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-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
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-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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diff --git a/docs/reference/add_any_miss.html b/docs/reference/add_any_miss.html
deleted file mode 100644
index dab951e5..00000000
--- a/docs/reference/add_any_miss.html
+++ /dev/null
@@ -1,197 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content='This adds a column named "any_miss" (by default) that describes whether
-there are any missings in all of the variables (default), or whether any
-of the specified columns, specified using variables names or dplyr verbs,
-starts_with, contains, ends_with, etc. By default the added column
-will be called "any_miss_all", if no variables are specified, otherwise,
-if variables are specified, the label will be "any_miss_vars" to indicate
-that not all variables have been used to create the labels.'><title>Add a column describing presence of any missing values — add_any_miss • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Add a column describing presence of any missing values — add_any_miss"><meta property="og:description" content='This adds a column named "any_miss" (by default) that describes whether
-there are any missings in all of the variables (default), or whether any
-of the specified columns, specified using variables names or dplyr verbs,
-starts_with, contains, ends_with, etc. By default the added column
-will be called "any_miss_all", if no variables are specified, otherwise,
-if variables are specified, the label will be "any_miss_vars" to indicate
-that not all variables have been used to create the labels.'><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
-<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
-<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
-<![endif]--></head><body>
-    <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
-    
-
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-primary"><div class="container">
-    
-    <a class="navbar-brand me-2" href="../index.html">naniar</a>
-
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0.9000</small>
-
-    
-    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
-      <span class="navbar-toggler-icon"></span>
-    </button>
-
-    <div id="navbar" class="collapse navbar-collapse ms-3">
-      <ul class="navbar-nav me-auto"><li class="nav-item">
-  <a class="nav-link" href="../articles/getting-started-w-naniar.html">Getting Started</a>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../articles/naniar-visualisation.html">Gallery</a>
-</li>
-<li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown-articles">Articles</a>
-  <div class="dropdown-menu" aria-labelledby="dropdown-articles">
-    <a class="dropdown-item" href="../articles/replace-with-na.html">Replace with NA</a>
-    <a class="dropdown-item" href="../articles/special-missing-values.html">Special Missings</a>
-    <a class="dropdown-item" href="../articles/exploring-imputed-values.html">Exploring Imputations</a>
-  </div>
-</li>
-<li class="active nav-item">
-  <a class="nav-link" href="../reference/index.html">Reference</a>
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-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
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-  <a class="external-link nav-link" href="https://github.com/njtierney/naniar/" aria-label="github">
-    <span class="fab fa fab fa-github fa-lg"></span>
-     
-  </a>
-</li>
-      </ul></div>
-
-    
-  </div>
-</nav><div class="container template-reference-topic">
-<div class="row">
-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Add a column describing presence of any missing values</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/add-cols.R" class="external-link"><code>R/add-cols.R</code></a></small>
-      <div class="d-none name"><code>add_any_miss.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>This adds a column named "any_miss" (by default) that describes whether
-there are any missings in all of the variables (default), or whether any
-of the specified columns, specified using variables names or dplyr verbs,
-<code>starts_with</code>, <code>contains</code>, <code>ends_with</code>, etc. By default the added column
-will be called "any_miss_all", if no variables are specified, otherwise,
-if variables are specified, the label will be "any_miss_vars" to indicate
-that not all variables have been used to create the labels.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">add_any_miss</span><span class="op">(</span></span>
-<span>  <span class="va">data</span>,</span>
-<span>  <span class="va">...</span>,</span>
-<span>  label <span class="op">=</span> <span class="st">"any_miss"</span>,</span>
-<span>  missing <span class="op">=</span> <span class="st">"missing"</span>,</span>
-<span>  complete <span class="op">=</span> <span class="st">"complete"</span></span>
-<span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>data.frame</p></dd>
-
-
-<dt>...</dt>
-<dd><p>Variable names to use instead of the whole dataset. By default this
-looks at the whole dataset. Otherwise, this is one or more unquoted
-expressions separated by commas. These also respect the dplyr verbs
-<code>starts_with</code>, <code>contains</code>, <code>ends_with</code>, etc. By default will add "_all" to
-the label if left blank, otherwise will add "_vars" to distinguish that it
-has not been used on all of the variables.</p></dd>
-
-
-<dt>label</dt>
-<dd><p>label for the column, defaults to "any_miss". By default if no
-additional variables are listed the label col is "any_miss_all", otherwise
-it is "any_miss_vars", if variables are specified.</p></dd>
-
-
-<dt>missing</dt>
-<dd><p>character a label for when values are missing - defaults to "missing"</p></dd>
-
-
-<dt>complete</dt>
-<dd><p>character character a label for when values are complete - defaults to "complete"</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>data.frame with data and the column labelling whether that row (for
-those variables) has any missing values - indicated by "missing" and
-"complete".</p>
-    </div>
-    <div class="section level2">
-    <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
-    <p>By default the
-prefix "any_miss" is used, but this can be changed in the <code>label</code> argument.</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="bind_shadow.html">bind_shadow()</a></code> <code>add_any_miss()</code> <code><a href="add_label_missings.html">add_label_missings()</a></code> <code><a href="add_label_shadow.html">add_label_shadow()</a></code> <code><a href="add_miss_cluster.html">add_miss_cluster()</a></code> <code><a href="add_n_miss.html">add_n_miss()</a></code> <code><a href="add_prop_miss.html">add_prop_miss()</a></code> <code><a href="add_shadow_shift.html">add_shadow_shift()</a></code> <code><a href="cast_shadow.html">cast_shadow()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu">add_any_miss</span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 7</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    Ozone Solar.R  Wind  Temp Month   Day any_miss_all</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>    41     190   7.4    67     5     1 complete    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>    36     118   8      72     5     2 complete    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>    12     149  12.6    74     5     3 complete    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>    18     313  11.5    62     5     4 complete    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>    <span style="color: #BB0000;">NA</span>      <span style="color: #BB0000;">NA</span>  14.3    56     5     5 missing     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>    28      <span style="color: #BB0000;">NA</span>  14.9    66     5     6 missing     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>    23     299   8.6    65     5     7 complete    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>    19      99  13.8    59     5     8 complete    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>     8      19  20.1    61     5     9 complete    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>    <span style="color: #BB0000;">NA</span>     194   8.6    69     5    10 missing     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu">add_any_miss</span><span class="op">(</span><span class="va">Ozone</span>, <span class="va">Solar.R</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 7</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    Ozone Solar.R  Wind  Temp Month   Day any_miss_vars</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>        </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>    41     190   7.4    67     5     1 complete     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>    36     118   8      72     5     2 complete     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>    12     149  12.6    74     5     3 complete     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>    18     313  11.5    62     5     4 complete     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>    <span style="color: #BB0000;">NA</span>      <span style="color: #BB0000;">NA</span>  14.3    56     5     5 missing      </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>    28      <span style="color: #BB0000;">NA</span>  14.9    66     5     6 missing      </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>    23     299   8.6    65     5     7 complete     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>    19      99  13.8    59     5     8 complete     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>     8      19  20.1    61     5     9 complete     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>    <span style="color: #BB0000;">NA</span>     194   8.6    69     5    10 missing      </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/add_label_missings.html b/docs/reference/add_label_missings.html
deleted file mode 100644
index 94f77ccd..00000000
--- a/docs/reference/add_label_missings.html
+++ /dev/null
@@ -1,171 +0,0 @@
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-      <img src="../logo.png" class="logo" alt=""><h1>Add a column describing if there are any missings in the dataset</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/add-cols.R" class="external-link"><code>R/add-cols.R</code></a></small>
-      <div class="d-none name"><code>add_label_missings.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Add a column describing if there are any missings in the dataset</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">add_label_missings</span><span class="op">(</span><span class="va">data</span>, <span class="va">...</span>, missing <span class="op">=</span> <span class="st">"Missing"</span>, complete <span class="op">=</span> <span class="st">"Not Missing"</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>data.frame</p></dd>
-
-
-<dt>...</dt>
-<dd><p>extra variable to label</p></dd>
-
-
-<dt>missing</dt>
-<dd><p>character a label for when values are missing - defaults to "Missing"</p></dd>
-
-
-<dt>complete</dt>
-<dd><p>character character a label for when values are complete - defaults to "Not Missing"</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>data.frame with a column "any_missing" that is either "Not Missing"
-or "Missing" for the purposes of plotting / exploration / nice print methods</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="bind_shadow.html">bind_shadow()</a></code> <code><a href="add_any_miss.html">add_any_miss()</a></code> <code>add_label_missings()</code> <code><a href="add_label_shadow.html">add_label_shadow()</a></code> <code><a href="add_miss_cluster.html">add_miss_cluster()</a></code> <code><a href="add_n_miss.html">add_n_miss()</a></code> <code><a href="add_prop_miss.html">add_prop_miss()</a></code> <code><a href="add_shadow_shift.html">add_shadow_shift()</a></code> <code><a href="cast_shadow.html">cast_shadow()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu">add_label_missings</span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 7</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    Ozone Solar.R  Wind  Temp Month   Day any_missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>      </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>    41     190   7.4    67     5     1 Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>    36     118   8      72     5     2 Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>    12     149  12.6    74     5     3 Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>    18     313  11.5    62     5     4 Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>    <span style="color: #BB0000;">NA</span>      <span style="color: #BB0000;">NA</span>  14.3    56     5     5 Missing    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>    28      <span style="color: #BB0000;">NA</span>  14.9    66     5     6 Missing    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>    23     299   8.6    65     5     7 Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>    19      99  13.8    59     5     8 Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>     8      19  20.1    61     5     9 Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>    <span style="color: #BB0000;">NA</span>     194   8.6    69     5    10 Missing    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu">add_label_missings</span><span class="op">(</span><span class="va">Ozone</span>, <span class="va">Solar.R</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 7</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    Ozone Solar.R  Wind  Temp Month   Day any_missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>      </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>    41     190   7.4    67     5     1 Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>    36     118   8      72     5     2 Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>    12     149  12.6    74     5     3 Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>    18     313  11.5    62     5     4 Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>    <span style="color: #BB0000;">NA</span>      <span style="color: #BB0000;">NA</span>  14.3    56     5     5 Missing    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>    28      <span style="color: #BB0000;">NA</span>  14.9    66     5     6 Missing    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>    23     299   8.6    65     5     7 Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>    19      99  13.8    59     5     8 Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>     8      19  20.1    61     5     9 Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>    <span style="color: #BB0000;">NA</span>     194   8.6    69     5    10 Missing    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu">add_label_missings</span><span class="op">(</span><span class="va">Ozone</span>, <span class="va">Solar.R</span>, missing <span class="op">=</span> <span class="st">"yes"</span>, complete <span class="op">=</span> <span class="st">"no"</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 7</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    Ozone Solar.R  Wind  Temp Month   Day any_missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>      </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>    41     190   7.4    67     5     1 no         </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>    36     118   8      72     5     2 no         </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>    12     149  12.6    74     5     3 no         </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>    18     313  11.5    62     5     4 no         </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>    <span style="color: #BB0000;">NA</span>      <span style="color: #BB0000;">NA</span>  14.3    56     5     5 yes        </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>    28      <span style="color: #BB0000;">NA</span>  14.9    66     5     6 yes        </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>    23     299   8.6    65     5     7 no         </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>    19      99  13.8    59     5     8 no         </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>     8      19  20.1    61     5     9 no         </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>    <span style="color: #BB0000;">NA</span>     194   8.6    69     5    10 yes        </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
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diff --git a/docs/reference/add_label_shadow.html b/docs/reference/add_label_shadow.html
deleted file mode 100644
index ea155505..00000000
--- a/docs/reference/add_label_shadow.html
+++ /dev/null
@@ -1,152 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Instead of focussing on labelling whether there are missings, we instead
-focus on whether there have been any shadows created. This can be useful
-when data has been imputed and you need to determine which rows contained
-missing values when the shadow was bound to the dataset."><title>Add a column describing whether there is a shadow — add_label_shadow • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Add a column describing whether there is a shadow — add_label_shadow"><meta property="og:description" content="Instead of focussing on labelling whether there are missings, we instead
-focus on whether there have been any shadows created. This can be useful
-when data has been imputed and you need to determine which rows contained
-missing values when the shadow was bound to the dataset."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
-<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
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-    <a class="dropdown-item" href="../articles/replace-with-na.html">Replace with NA</a>
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-      <img src="../logo.png" class="logo" alt=""><h1>Add a column describing whether there is a shadow</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/add-cols.R" class="external-link"><code>R/add-cols.R</code></a></small>
-      <div class="d-none name"><code>add_label_shadow.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Instead of focussing on labelling whether there are missings, we instead
-focus on whether there have been any shadows created. This can be useful
-when data has been imputed and you need to determine which rows contained
-missing values when the shadow was bound to the dataset.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">add_label_shadow</span><span class="op">(</span><span class="va">data</span>, <span class="va">...</span>, missing <span class="op">=</span> <span class="st">"Missing"</span>, complete <span class="op">=</span> <span class="st">"Not Missing"</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>data.frame</p></dd>
-
-
-<dt>...</dt>
-<dd><p>extra variable to label</p></dd>
-
-
-<dt>missing</dt>
-<dd><p>character a label for when values are missing - defaults to "Missing"</p></dd>
-
-
-<dt>complete</dt>
-<dd><p>character character a label for when values are complete - defaults to "Not Missing"</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>data.frame with a column, "any_missing", which describes whether or
-not there are any rows that have a shadow value.</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="bind_shadow.html">bind_shadow()</a></code> <code><a href="add_any_miss.html">add_any_miss()</a></code> <code><a href="add_label_missings.html">add_label_missings()</a></code> <code>add_label_shadow()</code> <code><a href="add_miss_cluster.html">add_miss_cluster()</a></code> <code><a href="add_n_miss.html">add_n_miss()</a></code> <code><a href="add_prop_miss.html">add_prop_miss()</a></code> <code><a href="add_shadow_shift.html">add_shadow_shift()</a></code> <code><a href="cast_shadow.html">cast_shadow()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="add_shadow.html">add_shadow</a></span><span class="op">(</span><span class="va">Ozone</span>, <span class="va">Solar.R</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu">add_label_shadow</span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 9</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    Ozone Solar.R  Wind  Temp Month   Day Ozone_NA Solar.R_NA any_missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>      </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>    41     190   7.4    67     5     1 !NA      !NA        Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>    36     118   8      72     5     2 !NA      !NA        Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>    12     149  12.6    74     5     3 !NA      !NA        Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>    18     313  11.5    62     5     4 !NA      !NA        Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>    <span style="color: #BB0000;">NA</span>      <span style="color: #BB0000;">NA</span>  14.3    56     5     5 NA       NA         Missing    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>    28      <span style="color: #BB0000;">NA</span>  14.9    66     5     6 !NA      NA         Missing    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>    23     299   8.6    65     5     7 !NA      !NA        Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>    19      99  13.8    59     5     8 !NA      !NA        Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>     8      19  20.1    61     5     9 !NA      !NA        Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>    <span style="color: #BB0000;">NA</span>     194   8.6    69     5    10 NA       !NA        Missing    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
-
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-    <footer><div class="pkgdown-footer-left">
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diff --git a/docs/reference/add_miss_cluster.html b/docs/reference/add_miss_cluster.html
deleted file mode 100644
index cddaa27c..00000000
--- a/docs/reference/add_miss_cluster.html
+++ /dev/null
@@ -1,175 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="A way to extract the cluster of missingness that a group belongs to.
-For example, if you use vis_miss(airquality, cluster = TRUE), you can
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-For example, if you use vis_miss(airquality, cluster = TRUE), you can
-see some clustering in the data, but you do not have a way to identify
-the cluster. Future work will incorporate the seriation package to
-allow for better control over the clustering from the user."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-      <img src="../logo.png" class="logo" alt=""><h1>Add a column that tells us which "missingness cluster" a row belongs to</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/add-cols.R" class="external-link"><code>R/add-cols.R</code></a></small>
-      <div class="d-none name"><code>add_miss_cluster.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>A way to extract the cluster of missingness that a group belongs to.
-For example, if you use <code>vis_miss(airquality, cluster = TRUE)</code>, you can
-see some clustering in the data, but you do not have a way to identify
-the cluster. Future work will incorporate the <code>seriation</code> package to
-allow for better control over the clustering from the user.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">add_miss_cluster</span><span class="op">(</span><span class="va">data</span>, cluster_method <span class="op">=</span> <span class="st">"mcquitty"</span>, n_clusters <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>a dataframe</p></dd>
-
-
-<dt>cluster_method</dt>
-<dd><p>character vector of the agglomeration method to use,
-the default is "mcquitty". Options are taken from <code><a href="https://rdrr.io/r/stats/hclust.html" class="external-link">stats::hclust</a></code>
-helpfile, and options include: "ward.D", "ward.D2", "single", "complete",
-"average" (= UPGMA), "mcquitty" (= WPGMA), "median" (= WPGMC) or
-"centroid" (= UPGMC).</p></dd>
-
-
-<dt>n_clusters</dt>
-<dd><p>numeric the number of clusters you expect. Defaults to 2.</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="bind_shadow.html">bind_shadow()</a></code> <code><a href="add_any_miss.html">add_any_miss()</a></code> <code><a href="add_label_missings.html">add_label_missings()</a></code> <code><a href="add_label_shadow.html">add_label_shadow()</a></code> <code>add_miss_cluster()</code> <code><a href="add_n_miss.html">add_n_miss()</a></code> <code><a href="add_prop_miss.html">add_prop_miss()</a></code> <code><a href="add_shadow_shift.html">add_shadow_shift()</a></code> <code><a href="cast_shadow.html">cast_shadow()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">add_miss_cluster</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 7</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    Ozone Solar.R  Wind  Temp Month   Day miss_cluster</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>        <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>    41     190   7.4    67     5     1            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>    36     118   8      72     5     2            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>    12     149  12.6    74     5     3            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>    18     313  11.5    62     5     4            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>    <span style="color: #BB0000;">NA</span>      <span style="color: #BB0000;">NA</span>  14.3    56     5     5            2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>    28      <span style="color: #BB0000;">NA</span>  14.9    66     5     6            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>    23     299   8.6    65     5     7            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>    19      99  13.8    59     5     8            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>     8      19  20.1    61     5     9            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>    <span style="color: #BB0000;">NA</span>     194   8.6    69     5    10            2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-<span class="r-in"><span><span class="fu">add_miss_cluster</span><span class="op">(</span><span class="va">airquality</span>, n_clusters <span class="op">=</span> <span class="fl">3</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 7</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    Ozone Solar.R  Wind  Temp Month   Day miss_cluster</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>        <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>    41     190   7.4    67     5     1            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>    36     118   8      72     5     2            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>    12     149  12.6    74     5     3            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>    18     313  11.5    62     5     4            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>    <span style="color: #BB0000;">NA</span>      <span style="color: #BB0000;">NA</span>  14.3    56     5     5            2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>    28      <span style="color: #BB0000;">NA</span>  14.9    66     5     6            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>    23     299   8.6    65     5     7            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>    19      99  13.8    59     5     8            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>     8      19  20.1    61     5     9            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>    <span style="color: #BB0000;">NA</span>     194   8.6    69     5    10            3</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-<span class="r-in"><span><span class="fu">add_miss_cluster</span><span class="op">(</span><span class="va">airquality</span>, cluster_method <span class="op">=</span> <span class="st">"ward.D"</span>, n_clusters <span class="op">=</span> <span class="fl">3</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 7</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    Ozone Solar.R  Wind  Temp Month   Day miss_cluster</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>        <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>    41     190   7.4    67     5     1            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>    36     118   8      72     5     2            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>    12     149  12.6    74     5     3            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>    18     313  11.5    62     5     4            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>    <span style="color: #BB0000;">NA</span>      <span style="color: #BB0000;">NA</span>  14.3    56     5     5            2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>    28      <span style="color: #BB0000;">NA</span>  14.9    66     5     6            2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>    23     299   8.6    65     5     7            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>    19      99  13.8    59     5     8            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>     8      19  20.1    61     5     9            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>    <span style="color: #BB0000;">NA</span>     194   8.6    69     5    10            3</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-</code></pre></div>
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diff --git a/docs/reference/add_n_miss.html b/docs/reference/add_n_miss.html
deleted file mode 100644
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--- a/docs/reference/add_n_miss.html
+++ /dev/null
@@ -1,598 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content='It can be useful when doing data analysis to add the number of missing data
-points into your dataframe. add_n_miss adds a column named "n_miss",
-which contains the number of missing values in that row.'><title>Add column containing number of missing data values — add_n_miss • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Add column containing number of missing data values — add_n_miss"><meta property="og:description" content='It can be useful when doing data analysis to add the number of missing data
-points into your dataframe. add_n_miss adds a column named "n_miss",
-which contains the number of missing values in that row.'><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-      <img src="../logo.png" class="logo" alt=""><h1>Add column containing number of missing data values</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/add-n-prop-miss.R" class="external-link"><code>R/add-n-prop-miss.R</code></a></small>
-      <div class="d-none name"><code>add_n_miss.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>It can be useful when doing data analysis to add the number of missing data
-points into your dataframe. <code>add_n_miss</code> adds a column named "n_miss",
-which contains the number of missing values in that row.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">add_n_miss</span><span class="op">(</span><span class="va">data</span>, <span class="va">...</span>, label <span class="op">=</span> <span class="st">"n_miss"</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>a dataframe</p></dd>
-
-
-<dt>...</dt>
-<dd><p>Variable names to use instead of the whole dataset. By default this
-looks at the whole dataset. Otherwise, this is one or more unquoted
-expressions separated by commas. These also respect the dplyr verbs
-<code>starts_with</code>, <code>contains</code>, <code>ends_with</code>, etc. By default will add "_all" to
-the label if left blank, otherwise will add "_vars" to distinguish that it
-has not been used on all of the variables.</p></dd>
-
-
-<dt>label</dt>
-<dd><p>character default is "n_miss".</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>a dataframe</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="bind_shadow.html">bind_shadow()</a></code> <code><a href="add_any_miss.html">add_any_miss()</a></code> <code><a href="add_label_missings.html">add_label_missings()</a></code> <code><a href="add_label_shadow.html">add_label_shadow()</a></code> <code><a href="add_miss_cluster.html">add_miss_cluster()</a></code> <code><a href="add_prop_miss.html">add_prop_miss()</a></code> <code><a href="add_shadow_shift.html">add_shadow_shift()</a></code> <code><a href="cast_shadow.html">cast_shadow()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu">add_n_miss</span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>     Ozone Solar.R Wind Temp Month Day n_miss_all</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 1      41     190  7.4   67     5   1          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 2      36     118  8.0   72     5   2          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 3      12     149 12.6   74     5   3          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 4      18     313 11.5   62     5   4          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 5      NA      NA 14.3   56     5   5          2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 6      28      NA 14.9   66     5   6          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 7      23     299  8.6   65     5   7          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 8      19      99 13.8   59     5   8          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 9       8      19 20.1   61     5   9          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 10     NA     194  8.6   69     5  10          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 11      7      NA  6.9   74     5  11          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 12     16     256  9.7   69     5  12          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 13     11     290  9.2   66     5  13          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 14     14     274 10.9   68     5  14          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 15     18      65 13.2   58     5  15          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 16     14     334 11.5   64     5  16          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 17     34     307 12.0   66     5  17          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 18      6      78 18.4   57     5  18          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 19     30     322 11.5   68     5  19          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 20     11      44  9.7   62     5  20          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 21      1       8  9.7   59     5  21          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 22     11     320 16.6   73     5  22          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 23      4      25  9.7   61     5  23          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 24     32      92 12.0   61     5  24          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 25     NA      66 16.6   57     5  25          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 26     NA     266 14.9   58     5  26          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 27     NA      NA  8.0   57     5  27          2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 28     23      13 12.0   67     5  28          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 29     45     252 14.9   81     5  29          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 30    115     223  5.7   79     5  30          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 31     37     279  7.4   76     5  31          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 32     NA     286  8.6   78     6   1          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 33     NA     287  9.7   74     6   2          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 34     NA     242 16.1   67     6   3          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 35     NA     186  9.2   84     6   4          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 36     NA     220  8.6   85     6   5          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 37     NA     264 14.3   79     6   6          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 38     29     127  9.7   82     6   7          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 39     NA     273  6.9   87     6   8          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 40     71     291 13.8   90     6   9          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 41     39     323 11.5   87     6  10          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 42     NA     259 10.9   93     6  11          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 43     NA     250  9.2   92     6  12          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 44     23     148  8.0   82     6  13          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 45     NA     332 13.8   80     6  14          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 46     NA     322 11.5   79     6  15          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 47     21     191 14.9   77     6  16          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 48     37     284 20.7   72     6  17          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 49     20      37  9.2   65     6  18          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 50     12     120 11.5   73     6  19          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 51     13     137 10.3   76     6  20          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 52     NA     150  6.3   77     6  21          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 53     NA      59  1.7   76     6  22          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 54     NA      91  4.6   76     6  23          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 55     NA     250  6.3   76     6  24          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 56     NA     135  8.0   75     6  25          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 57     NA     127  8.0   78     6  26          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 58     NA      47 10.3   73     6  27          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 59     NA      98 11.5   80     6  28          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 60     NA      31 14.9   77     6  29          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 61     NA     138  8.0   83     6  30          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 62    135     269  4.1   84     7   1          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 63     49     248  9.2   85     7   2          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 64     32     236  9.2   81     7   3          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 65     NA     101 10.9   84     7   4          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 66     64     175  4.6   83     7   5          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 67     40     314 10.9   83     7   6          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 68     77     276  5.1   88     7   7          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 69     97     267  6.3   92     7   8          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 70     97     272  5.7   92     7   9          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 71     85     175  7.4   89     7  10          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 72     NA     139  8.6   82     7  11          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 73     10     264 14.3   73     7  12          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 74     27     175 14.9   81     7  13          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 75     NA     291 14.9   91     7  14          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 76      7      48 14.3   80     7  15          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 77     48     260  6.9   81     7  16          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 78     35     274 10.3   82     7  17          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 79     61     285  6.3   84     7  18          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 80     79     187  5.1   87     7  19          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 81     63     220 11.5   85     7  20          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 82     16       7  6.9   74     7  21          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 83     NA     258  9.7   81     7  22          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 84     NA     295 11.5   82     7  23          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 85     80     294  8.6   86     7  24          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 86    108     223  8.0   85     7  25          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 87     20      81  8.6   82     7  26          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 88     52      82 12.0   86     7  27          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 89     82     213  7.4   88     7  28          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 90     50     275  7.4   86     7  29          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 91     64     253  7.4   83     7  30          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 92     59     254  9.2   81     7  31          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 93     39      83  6.9   81     8   1          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 94      9      24 13.8   81     8   2          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 95     16      77  7.4   82     8   3          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 96     78      NA  6.9   86     8   4          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 97     35      NA  7.4   85     8   5          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 98     66      NA  4.6   87     8   6          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 99    122     255  4.0   89     8   7          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 100    89     229 10.3   90     8   8          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 101   110     207  8.0   90     8   9          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 102    NA     222  8.6   92     8  10          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 103    NA     137 11.5   86     8  11          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 104    44     192 11.5   86     8  12          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 105    28     273 11.5   82     8  13          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 106    65     157  9.7   80     8  14          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 107    NA      64 11.5   79     8  15          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 108    22      71 10.3   77     8  16          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 109    59      51  6.3   79     8  17          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 110    23     115  7.4   76     8  18          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 111    31     244 10.9   78     8  19          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 112    44     190 10.3   78     8  20          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 113    21     259 15.5   77     8  21          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 114     9      36 14.3   72     8  22          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 115    NA     255 12.6   75     8  23          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 116    45     212  9.7   79     8  24          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 117   168     238  3.4   81     8  25          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 118    73     215  8.0   86     8  26          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 119    NA     153  5.7   88     8  27          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 120    76     203  9.7   97     8  28          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 121   118     225  2.3   94     8  29          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 122    84     237  6.3   96     8  30          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 123    85     188  6.3   94     8  31          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 124    96     167  6.9   91     9   1          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 125    78     197  5.1   92     9   2          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 126    73     183  2.8   93     9   3          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 127    91     189  4.6   93     9   4          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 128    47      95  7.4   87     9   5          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 129    32      92 15.5   84     9   6          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 130    20     252 10.9   80     9   7          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 131    23     220 10.3   78     9   8          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 132    21     230 10.9   75     9   9          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 133    24     259  9.7   73     9  10          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 134    44     236 14.9   81     9  11          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 135    21     259 15.5   76     9  12          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 136    28     238  6.3   77     9  13          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 137     9      24 10.9   71     9  14          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 138    13     112 11.5   71     9  15          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 139    46     237  6.9   78     9  16          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 140    18     224 13.8   67     9  17          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 141    13      27 10.3   76     9  18          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 142    24     238 10.3   68     9  19          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 143    16     201  8.0   82     9  20          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 144    13     238 12.6   64     9  21          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 145    23      14  9.2   71     9  22          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 146    36     139 10.3   81     9  23          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 147     7      49 10.3   69     9  24          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 148    14      20 16.6   63     9  25          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 149    30     193  6.9   70     9  26          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 150    NA     145 13.2   77     9  27          1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 151    14     191 14.3   75     9  28          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 152    18     131  8.0   76     9  29          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 153    20     223 11.5   68     9  30          0</span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu">add_n_miss</span><span class="op">(</span><span class="va">Ozone</span>, <span class="va">Solar.R</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>     Ozone Solar.R Wind Temp Month Day n_miss_vars</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 1      41     190  7.4   67     5   1           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 2      36     118  8.0   72     5   2           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 3      12     149 12.6   74     5   3           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 4      18     313 11.5   62     5   4           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 5      NA      NA 14.3   56     5   5           2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 6      28      NA 14.9   66     5   6           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 7      23     299  8.6   65     5   7           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 8      19      99 13.8   59     5   8           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 9       8      19 20.1   61     5   9           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 10     NA     194  8.6   69     5  10           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 11      7      NA  6.9   74     5  11           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 12     16     256  9.7   69     5  12           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 13     11     290  9.2   66     5  13           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 14     14     274 10.9   68     5  14           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 15     18      65 13.2   58     5  15           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 16     14     334 11.5   64     5  16           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 17     34     307 12.0   66     5  17           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 18      6      78 18.4   57     5  18           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 19     30     322 11.5   68     5  19           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 20     11      44  9.7   62     5  20           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 21      1       8  9.7   59     5  21           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 22     11     320 16.6   73     5  22           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 23      4      25  9.7   61     5  23           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 24     32      92 12.0   61     5  24           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 25     NA      66 16.6   57     5  25           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 26     NA     266 14.9   58     5  26           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 27     NA      NA  8.0   57     5  27           2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 28     23      13 12.0   67     5  28           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 29     45     252 14.9   81     5  29           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 30    115     223  5.7   79     5  30           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 31     37     279  7.4   76     5  31           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 32     NA     286  8.6   78     6   1           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 33     NA     287  9.7   74     6   2           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 34     NA     242 16.1   67     6   3           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 35     NA     186  9.2   84     6   4           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 36     NA     220  8.6   85     6   5           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 37     NA     264 14.3   79     6   6           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 38     29     127  9.7   82     6   7           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 39     NA     273  6.9   87     6   8           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 40     71     291 13.8   90     6   9           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 41     39     323 11.5   87     6  10           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 42     NA     259 10.9   93     6  11           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 43     NA     250  9.2   92     6  12           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 44     23     148  8.0   82     6  13           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 45     NA     332 13.8   80     6  14           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 46     NA     322 11.5   79     6  15           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 47     21     191 14.9   77     6  16           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 48     37     284 20.7   72     6  17           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 49     20      37  9.2   65     6  18           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 50     12     120 11.5   73     6  19           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 51     13     137 10.3   76     6  20           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 52     NA     150  6.3   77     6  21           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 53     NA      59  1.7   76     6  22           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 54     NA      91  4.6   76     6  23           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 55     NA     250  6.3   76     6  24           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 56     NA     135  8.0   75     6  25           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 57     NA     127  8.0   78     6  26           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 58     NA      47 10.3   73     6  27           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 59     NA      98 11.5   80     6  28           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 60     NA      31 14.9   77     6  29           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 61     NA     138  8.0   83     6  30           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 62    135     269  4.1   84     7   1           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 63     49     248  9.2   85     7   2           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 64     32     236  9.2   81     7   3           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 65     NA     101 10.9   84     7   4           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 66     64     175  4.6   83     7   5           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 67     40     314 10.9   83     7   6           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 68     77     276  5.1   88     7   7           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 69     97     267  6.3   92     7   8           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 70     97     272  5.7   92     7   9           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 71     85     175  7.4   89     7  10           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 72     NA     139  8.6   82     7  11           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 73     10     264 14.3   73     7  12           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 74     27     175 14.9   81     7  13           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 75     NA     291 14.9   91     7  14           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 76      7      48 14.3   80     7  15           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 77     48     260  6.9   81     7  16           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 78     35     274 10.3   82     7  17           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 79     61     285  6.3   84     7  18           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 80     79     187  5.1   87     7  19           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 81     63     220 11.5   85     7  20           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 82     16       7  6.9   74     7  21           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 83     NA     258  9.7   81     7  22           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 84     NA     295 11.5   82     7  23           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 85     80     294  8.6   86     7  24           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 86    108     223  8.0   85     7  25           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 87     20      81  8.6   82     7  26           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 88     52      82 12.0   86     7  27           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 89     82     213  7.4   88     7  28           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 90     50     275  7.4   86     7  29           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 91     64     253  7.4   83     7  30           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 92     59     254  9.2   81     7  31           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 93     39      83  6.9   81     8   1           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 94      9      24 13.8   81     8   2           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 95     16      77  7.4   82     8   3           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 96     78      NA  6.9   86     8   4           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 97     35      NA  7.4   85     8   5           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 98     66      NA  4.6   87     8   6           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 99    122     255  4.0   89     8   7           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 100    89     229 10.3   90     8   8           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 101   110     207  8.0   90     8   9           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 102    NA     222  8.6   92     8  10           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 103    NA     137 11.5   86     8  11           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 104    44     192 11.5   86     8  12           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 105    28     273 11.5   82     8  13           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 106    65     157  9.7   80     8  14           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 107    NA      64 11.5   79     8  15           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 108    22      71 10.3   77     8  16           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 109    59      51  6.3   79     8  17           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 110    23     115  7.4   76     8  18           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 111    31     244 10.9   78     8  19           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 112    44     190 10.3   78     8  20           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 113    21     259 15.5   77     8  21           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 114     9      36 14.3   72     8  22           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 115    NA     255 12.6   75     8  23           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 116    45     212  9.7   79     8  24           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 117   168     238  3.4   81     8  25           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 118    73     215  8.0   86     8  26           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 119    NA     153  5.7   88     8  27           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 120    76     203  9.7   97     8  28           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 121   118     225  2.3   94     8  29           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 122    84     237  6.3   96     8  30           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 123    85     188  6.3   94     8  31           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 124    96     167  6.9   91     9   1           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 125    78     197  5.1   92     9   2           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 126    73     183  2.8   93     9   3           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 127    91     189  4.6   93     9   4           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 128    47      95  7.4   87     9   5           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 129    32      92 15.5   84     9   6           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 130    20     252 10.9   80     9   7           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 131    23     220 10.3   78     9   8           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 132    21     230 10.9   75     9   9           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 133    24     259  9.7   73     9  10           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 134    44     236 14.9   81     9  11           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 135    21     259 15.5   76     9  12           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 136    28     238  6.3   77     9  13           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 137     9      24 10.9   71     9  14           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 138    13     112 11.5   71     9  15           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 139    46     237  6.9   78     9  16           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 140    18     224 13.8   67     9  17           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 141    13      27 10.3   76     9  18           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 142    24     238 10.3   68     9  19           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 143    16     201  8.0   82     9  20           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 144    13     238 12.6   64     9  21           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 145    23      14  9.2   71     9  22           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 146    36     139 10.3   81     9  23           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 147     7      49 10.3   69     9  24           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 148    14      20 16.6   63     9  25           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 149    30     193  6.9   70     9  26           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 150    NA     145 13.2   77     9  27           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 151    14     191 14.3   75     9  28           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 152    18     131  8.0   76     9  29           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 153    20     223 11.5   68     9  30           0</span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu">add_n_miss</span><span class="op">(</span><span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://tidyselect.r-lib.org/reference/starts_with.html" class="external-link">contains</a></span><span class="op">(</span><span class="st">"o"</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>     Ozone Solar.R Wind Temp Month Day n_miss_vars</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 1      41     190  7.4   67     5   1           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 2      36     118  8.0   72     5   2           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 3      12     149 12.6   74     5   3           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 4      18     313 11.5   62     5   4           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 5      NA      NA 14.3   56     5   5           2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 6      28      NA 14.9   66     5   6           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 7      23     299  8.6   65     5   7           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 8      19      99 13.8   59     5   8           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 9       8      19 20.1   61     5   9           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 10     NA     194  8.6   69     5  10           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 11      7      NA  6.9   74     5  11           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 12     16     256  9.7   69     5  12           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 13     11     290  9.2   66     5  13           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 14     14     274 10.9   68     5  14           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 15     18      65 13.2   58     5  15           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 16     14     334 11.5   64     5  16           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 17     34     307 12.0   66     5  17           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 18      6      78 18.4   57     5  18           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 19     30     322 11.5   68     5  19           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 20     11      44  9.7   62     5  20           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 21      1       8  9.7   59     5  21           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 22     11     320 16.6   73     5  22           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 23      4      25  9.7   61     5  23           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 24     32      92 12.0   61     5  24           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 25     NA      66 16.6   57     5  25           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 26     NA     266 14.9   58     5  26           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 27     NA      NA  8.0   57     5  27           2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 28     23      13 12.0   67     5  28           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 29     45     252 14.9   81     5  29           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 30    115     223  5.7   79     5  30           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 31     37     279  7.4   76     5  31           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 32     NA     286  8.6   78     6   1           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 33     NA     287  9.7   74     6   2           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 34     NA     242 16.1   67     6   3           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 35     NA     186  9.2   84     6   4           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 36     NA     220  8.6   85     6   5           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 37     NA     264 14.3   79     6   6           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 38     29     127  9.7   82     6   7           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 39     NA     273  6.9   87     6   8           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 40     71     291 13.8   90     6   9           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 41     39     323 11.5   87     6  10           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 42     NA     259 10.9   93     6  11           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 43     NA     250  9.2   92     6  12           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 44     23     148  8.0   82     6  13           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 45     NA     332 13.8   80     6  14           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 46     NA     322 11.5   79     6  15           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 47     21     191 14.9   77     6  16           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 48     37     284 20.7   72     6  17           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 49     20      37  9.2   65     6  18           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 50     12     120 11.5   73     6  19           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 51     13     137 10.3   76     6  20           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 52     NA     150  6.3   77     6  21           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 53     NA      59  1.7   76     6  22           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 54     NA      91  4.6   76     6  23           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 55     NA     250  6.3   76     6  24           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 56     NA     135  8.0   75     6  25           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 57     NA     127  8.0   78     6  26           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 58     NA      47 10.3   73     6  27           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 59     NA      98 11.5   80     6  28           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 60     NA      31 14.9   77     6  29           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 61     NA     138  8.0   83     6  30           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 62    135     269  4.1   84     7   1           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 63     49     248  9.2   85     7   2           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 64     32     236  9.2   81     7   3           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 65     NA     101 10.9   84     7   4           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 66     64     175  4.6   83     7   5           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 67     40     314 10.9   83     7   6           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 68     77     276  5.1   88     7   7           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 69     97     267  6.3   92     7   8           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 70     97     272  5.7   92     7   9           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 71     85     175  7.4   89     7  10           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 72     NA     139  8.6   82     7  11           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 73     10     264 14.3   73     7  12           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 74     27     175 14.9   81     7  13           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 75     NA     291 14.9   91     7  14           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 76      7      48 14.3   80     7  15           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 77     48     260  6.9   81     7  16           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 78     35     274 10.3   82     7  17           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 79     61     285  6.3   84     7  18           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 80     79     187  5.1   87     7  19           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 81     63     220 11.5   85     7  20           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 82     16       7  6.9   74     7  21           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 83     NA     258  9.7   81     7  22           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 84     NA     295 11.5   82     7  23           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 85     80     294  8.6   86     7  24           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 86    108     223  8.0   85     7  25           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 87     20      81  8.6   82     7  26           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 88     52      82 12.0   86     7  27           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 89     82     213  7.4   88     7  28           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 90     50     275  7.4   86     7  29           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 91     64     253  7.4   83     7  30           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 92     59     254  9.2   81     7  31           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 93     39      83  6.9   81     8   1           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 94      9      24 13.8   81     8   2           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 95     16      77  7.4   82     8   3           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 96     78      NA  6.9   86     8   4           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 97     35      NA  7.4   85     8   5           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 98     66      NA  4.6   87     8   6           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 99    122     255  4.0   89     8   7           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 100    89     229 10.3   90     8   8           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 101   110     207  8.0   90     8   9           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 102    NA     222  8.6   92     8  10           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 103    NA     137 11.5   86     8  11           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 104    44     192 11.5   86     8  12           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 105    28     273 11.5   82     8  13           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 106    65     157  9.7   80     8  14           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 107    NA      64 11.5   79     8  15           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 108    22      71 10.3   77     8  16           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 109    59      51  6.3   79     8  17           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 110    23     115  7.4   76     8  18           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 111    31     244 10.9   78     8  19           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 112    44     190 10.3   78     8  20           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 113    21     259 15.5   77     8  21           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 114     9      36 14.3   72     8  22           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 115    NA     255 12.6   75     8  23           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 116    45     212  9.7   79     8  24           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 117   168     238  3.4   81     8  25           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 118    73     215  8.0   86     8  26           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 119    NA     153  5.7   88     8  27           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 120    76     203  9.7   97     8  28           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 121   118     225  2.3   94     8  29           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 122    84     237  6.3   96     8  30           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 123    85     188  6.3   94     8  31           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 124    96     167  6.9   91     9   1           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 125    78     197  5.1   92     9   2           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 126    73     183  2.8   93     9   3           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 127    91     189  4.6   93     9   4           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 128    47      95  7.4   87     9   5           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 129    32      92 15.5   84     9   6           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 130    20     252 10.9   80     9   7           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 131    23     220 10.3   78     9   8           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 132    21     230 10.9   75     9   9           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 133    24     259  9.7   73     9  10           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 134    44     236 14.9   81     9  11           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 135    21     259 15.5   76     9  12           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 136    28     238  6.3   77     9  13           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 137     9      24 10.9   71     9  14           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 138    13     112 11.5   71     9  15           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 139    46     237  6.9   78     9  16           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 140    18     224 13.8   67     9  17           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 141    13      27 10.3   76     9  18           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 142    24     238 10.3   68     9  19           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 143    16     201  8.0   82     9  20           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 144    13     238 12.6   64     9  21           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 145    23      14  9.2   71     9  22           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 146    36     139 10.3   81     9  23           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 147     7      49 10.3   69     9  24           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 148    14      20 16.6   63     9  25           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 149    30     193  6.9   70     9  26           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 150    NA     145 13.2   77     9  27           1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 151    14     191 14.3   75     9  28           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 152    18     131  8.0   76     9  29           0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 153    20     223 11.5   68     9  30           0</span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
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diff --git a/docs/reference/add_prop_miss.html b/docs/reference/add_prop_miss.html
deleted file mode 100644
index cddd7cc5..00000000
--- a/docs/reference/add_prop_miss.html
+++ /dev/null
@@ -1,607 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content='It can be useful when doing data analysis to add the proportion of missing
-data values into your dataframe. add_prop_miss adds a column named
-"prop_miss", which contains the proportion of missing values in that row.
-You can specify the variables that you would like to show the missingness
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-"prop_miss", which contains the proportion of missing values in that row.
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-for.'><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-<div class="row">
-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Add column containing proportion of missing data values</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/add-n-prop-miss.R" class="external-link"><code>R/add-n-prop-miss.R</code></a></small>
-      <div class="d-none name"><code>add_prop_miss.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>It can be useful when doing data analysis to add the proportion of missing
-data values into your dataframe. <code>add_prop_miss</code> adds a column named
-"prop_miss", which contains the proportion of missing values in that row.
-You can specify the variables that you would like to show the missingness
-for.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">add_prop_miss</span><span class="op">(</span><span class="va">data</span>, <span class="va">...</span>, label <span class="op">=</span> <span class="st">"prop_miss"</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>a dataframe</p></dd>
-
-
-<dt>...</dt>
-<dd><p>Variable names to use instead of the whole dataset. By default this
-looks at the whole dataset. Otherwise, this is one or more unquoted
-expressions separated by commas. These also respect the dplyr verbs
-<code>starts_with</code>, <code>contains</code>, <code>ends_with</code>, etc. By default will add "_all" to
-the label if left blank, otherwise will add "_vars" to distinguish that it
-has not been used on all of the variables.</p></dd>
-
-
-<dt>label</dt>
-<dd><p>character string of what you need to name variable</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>a dataframe</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="bind_shadow.html">bind_shadow()</a></code> <code><a href="add_any_miss.html">add_any_miss()</a></code> <code><a href="add_label_missings.html">add_label_missings()</a></code> <code><a href="add_label_shadow.html">add_label_shadow()</a></code> <code><a href="add_miss_cluster.html">add_miss_cluster()</a></code> <code>add_prop_miss()</code> <code><a href="add_shadow_shift.html">add_shadow_shift()</a></code> <code><a href="cast_shadow.html">cast_shadow()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu">add_prop_miss</span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>     Ozone Solar.R Wind Temp Month Day prop_miss_all</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 1      41     190  7.4   67     5   1     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 2      36     118  8.0   72     5   2     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 3      12     149 12.6   74     5   3     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 4      18     313 11.5   62     5   4     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 5      NA      NA 14.3   56     5   5     0.3333333</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 6      28      NA 14.9   66     5   6     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 7      23     299  8.6   65     5   7     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 8      19      99 13.8   59     5   8     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 9       8      19 20.1   61     5   9     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 10     NA     194  8.6   69     5  10     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 11      7      NA  6.9   74     5  11     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 12     16     256  9.7   69     5  12     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 13     11     290  9.2   66     5  13     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 14     14     274 10.9   68     5  14     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 15     18      65 13.2   58     5  15     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 16     14     334 11.5   64     5  16     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 17     34     307 12.0   66     5  17     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 18      6      78 18.4   57     5  18     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 19     30     322 11.5   68     5  19     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 20     11      44  9.7   62     5  20     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 21      1       8  9.7   59     5  21     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 22     11     320 16.6   73     5  22     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 23      4      25  9.7   61     5  23     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 24     32      92 12.0   61     5  24     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 25     NA      66 16.6   57     5  25     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 26     NA     266 14.9   58     5  26     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 27     NA      NA  8.0   57     5  27     0.3333333</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 28     23      13 12.0   67     5  28     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 29     45     252 14.9   81     5  29     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 30    115     223  5.7   79     5  30     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 31     37     279  7.4   76     5  31     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 32     NA     286  8.6   78     6   1     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 33     NA     287  9.7   74     6   2     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 34     NA     242 16.1   67     6   3     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 35     NA     186  9.2   84     6   4     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 36     NA     220  8.6   85     6   5     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 37     NA     264 14.3   79     6   6     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 38     29     127  9.7   82     6   7     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 39     NA     273  6.9   87     6   8     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 40     71     291 13.8   90     6   9     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 41     39     323 11.5   87     6  10     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 42     NA     259 10.9   93     6  11     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 43     NA     250  9.2   92     6  12     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 44     23     148  8.0   82     6  13     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 45     NA     332 13.8   80     6  14     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 46     NA     322 11.5   79     6  15     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 47     21     191 14.9   77     6  16     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 48     37     284 20.7   72     6  17     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 49     20      37  9.2   65     6  18     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 50     12     120 11.5   73     6  19     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 51     13     137 10.3   76     6  20     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 52     NA     150  6.3   77     6  21     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 53     NA      59  1.7   76     6  22     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 54     NA      91  4.6   76     6  23     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 55     NA     250  6.3   76     6  24     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 56     NA     135  8.0   75     6  25     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 57     NA     127  8.0   78     6  26     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 58     NA      47 10.3   73     6  27     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 59     NA      98 11.5   80     6  28     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 60     NA      31 14.9   77     6  29     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 61     NA     138  8.0   83     6  30     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 62    135     269  4.1   84     7   1     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 63     49     248  9.2   85     7   2     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 64     32     236  9.2   81     7   3     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 65     NA     101 10.9   84     7   4     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 66     64     175  4.6   83     7   5     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 67     40     314 10.9   83     7   6     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 68     77     276  5.1   88     7   7     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 69     97     267  6.3   92     7   8     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 70     97     272  5.7   92     7   9     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 71     85     175  7.4   89     7  10     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 72     NA     139  8.6   82     7  11     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 73     10     264 14.3   73     7  12     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 74     27     175 14.9   81     7  13     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 75     NA     291 14.9   91     7  14     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 76      7      48 14.3   80     7  15     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 77     48     260  6.9   81     7  16     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 78     35     274 10.3   82     7  17     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 79     61     285  6.3   84     7  18     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 80     79     187  5.1   87     7  19     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 81     63     220 11.5   85     7  20     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 82     16       7  6.9   74     7  21     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 83     NA     258  9.7   81     7  22     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 84     NA     295 11.5   82     7  23     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 85     80     294  8.6   86     7  24     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 86    108     223  8.0   85     7  25     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 87     20      81  8.6   82     7  26     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 88     52      82 12.0   86     7  27     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 89     82     213  7.4   88     7  28     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 90     50     275  7.4   86     7  29     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 91     64     253  7.4   83     7  30     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 92     59     254  9.2   81     7  31     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 93     39      83  6.9   81     8   1     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 94      9      24 13.8   81     8   2     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 95     16      77  7.4   82     8   3     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 96     78      NA  6.9   86     8   4     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 97     35      NA  7.4   85     8   5     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 98     66      NA  4.6   87     8   6     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 99    122     255  4.0   89     8   7     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 100    89     229 10.3   90     8   8     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 101   110     207  8.0   90     8   9     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 102    NA     222  8.6   92     8  10     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 103    NA     137 11.5   86     8  11     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 104    44     192 11.5   86     8  12     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 105    28     273 11.5   82     8  13     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 106    65     157  9.7   80     8  14     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 107    NA      64 11.5   79     8  15     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 108    22      71 10.3   77     8  16     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 109    59      51  6.3   79     8  17     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 110    23     115  7.4   76     8  18     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 111    31     244 10.9   78     8  19     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 112    44     190 10.3   78     8  20     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 113    21     259 15.5   77     8  21     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 114     9      36 14.3   72     8  22     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 115    NA     255 12.6   75     8  23     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 116    45     212  9.7   79     8  24     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 117   168     238  3.4   81     8  25     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 118    73     215  8.0   86     8  26     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 119    NA     153  5.7   88     8  27     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 120    76     203  9.7   97     8  28     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 121   118     225  2.3   94     8  29     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 122    84     237  6.3   96     8  30     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 123    85     188  6.3   94     8  31     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 124    96     167  6.9   91     9   1     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 125    78     197  5.1   92     9   2     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 126    73     183  2.8   93     9   3     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 127    91     189  4.6   93     9   4     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 128    47      95  7.4   87     9   5     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 129    32      92 15.5   84     9   6     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 130    20     252 10.9   80     9   7     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 131    23     220 10.3   78     9   8     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 132    21     230 10.9   75     9   9     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 133    24     259  9.7   73     9  10     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 134    44     236 14.9   81     9  11     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 135    21     259 15.5   76     9  12     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 136    28     238  6.3   77     9  13     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 137     9      24 10.9   71     9  14     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 138    13     112 11.5   71     9  15     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 139    46     237  6.9   78     9  16     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 140    18     224 13.8   67     9  17     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 141    13      27 10.3   76     9  18     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 142    24     238 10.3   68     9  19     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 143    16     201  8.0   82     9  20     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 144    13     238 12.6   64     9  21     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 145    23      14  9.2   71     9  22     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 146    36     139 10.3   81     9  23     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 147     7      49 10.3   69     9  24     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 148    14      20 16.6   63     9  25     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 149    30     193  6.9   70     9  26     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 150    NA     145 13.2   77     9  27     0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 151    14     191 14.3   75     9  28     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 152    18     131  8.0   76     9  29     0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 153    20     223 11.5   68     9  30     0.0000000</span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu">add_prop_miss</span><span class="op">(</span><span class="va">Solar.R</span>, <span class="va">Ozone</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>     Ozone Solar.R Wind Temp Month Day prop_miss_vars</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 1      41     190  7.4   67     5   1            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 2      36     118  8.0   72     5   2            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 3      12     149 12.6   74     5   3            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 4      18     313 11.5   62     5   4            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 5      NA      NA 14.3   56     5   5            1.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 6      28      NA 14.9   66     5   6            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 7      23     299  8.6   65     5   7            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 8      19      99 13.8   59     5   8            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 9       8      19 20.1   61     5   9            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 10     NA     194  8.6   69     5  10            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 11      7      NA  6.9   74     5  11            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 12     16     256  9.7   69     5  12            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 13     11     290  9.2   66     5  13            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 14     14     274 10.9   68     5  14            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 15     18      65 13.2   58     5  15            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 16     14     334 11.5   64     5  16            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 17     34     307 12.0   66     5  17            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 18      6      78 18.4   57     5  18            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 19     30     322 11.5   68     5  19            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 20     11      44  9.7   62     5  20            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 21      1       8  9.7   59     5  21            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 22     11     320 16.6   73     5  22            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 23      4      25  9.7   61     5  23            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 24     32      92 12.0   61     5  24            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 25     NA      66 16.6   57     5  25            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 26     NA     266 14.9   58     5  26            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 27     NA      NA  8.0   57     5  27            1.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 28     23      13 12.0   67     5  28            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 29     45     252 14.9   81     5  29            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 30    115     223  5.7   79     5  30            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 31     37     279  7.4   76     5  31            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 32     NA     286  8.6   78     6   1            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 33     NA     287  9.7   74     6   2            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 34     NA     242 16.1   67     6   3            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 35     NA     186  9.2   84     6   4            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 36     NA     220  8.6   85     6   5            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 37     NA     264 14.3   79     6   6            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 38     29     127  9.7   82     6   7            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 39     NA     273  6.9   87     6   8            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 40     71     291 13.8   90     6   9            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 41     39     323 11.5   87     6  10            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 42     NA     259 10.9   93     6  11            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 43     NA     250  9.2   92     6  12            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 44     23     148  8.0   82     6  13            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 45     NA     332 13.8   80     6  14            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 46     NA     322 11.5   79     6  15            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 47     21     191 14.9   77     6  16            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 48     37     284 20.7   72     6  17            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 49     20      37  9.2   65     6  18            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 50     12     120 11.5   73     6  19            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 51     13     137 10.3   76     6  20            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 52     NA     150  6.3   77     6  21            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 53     NA      59  1.7   76     6  22            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 54     NA      91  4.6   76     6  23            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 55     NA     250  6.3   76     6  24            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 56     NA     135  8.0   75     6  25            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 57     NA     127  8.0   78     6  26            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 58     NA      47 10.3   73     6  27            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 59     NA      98 11.5   80     6  28            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 60     NA      31 14.9   77     6  29            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 61     NA     138  8.0   83     6  30            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 62    135     269  4.1   84     7   1            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 63     49     248  9.2   85     7   2            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 64     32     236  9.2   81     7   3            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 65     NA     101 10.9   84     7   4            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 66     64     175  4.6   83     7   5            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 67     40     314 10.9   83     7   6            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 68     77     276  5.1   88     7   7            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 69     97     267  6.3   92     7   8            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 70     97     272  5.7   92     7   9            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 71     85     175  7.4   89     7  10            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 72     NA     139  8.6   82     7  11            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 73     10     264 14.3   73     7  12            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 74     27     175 14.9   81     7  13            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 75     NA     291 14.9   91     7  14            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 76      7      48 14.3   80     7  15            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 77     48     260  6.9   81     7  16            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 78     35     274 10.3   82     7  17            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 79     61     285  6.3   84     7  18            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 80     79     187  5.1   87     7  19            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 81     63     220 11.5   85     7  20            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 82     16       7  6.9   74     7  21            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 83     NA     258  9.7   81     7  22            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 84     NA     295 11.5   82     7  23            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 85     80     294  8.6   86     7  24            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 86    108     223  8.0   85     7  25            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 87     20      81  8.6   82     7  26            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 88     52      82 12.0   86     7  27            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 89     82     213  7.4   88     7  28            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 90     50     275  7.4   86     7  29            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 91     64     253  7.4   83     7  30            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 92     59     254  9.2   81     7  31            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 93     39      83  6.9   81     8   1            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 94      9      24 13.8   81     8   2            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 95     16      77  7.4   82     8   3            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 96     78      NA  6.9   86     8   4            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 97     35      NA  7.4   85     8   5            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 98     66      NA  4.6   87     8   6            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 99    122     255  4.0   89     8   7            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 100    89     229 10.3   90     8   8            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 101   110     207  8.0   90     8   9            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 102    NA     222  8.6   92     8  10            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 103    NA     137 11.5   86     8  11            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 104    44     192 11.5   86     8  12            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 105    28     273 11.5   82     8  13            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 106    65     157  9.7   80     8  14            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 107    NA      64 11.5   79     8  15            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 108    22      71 10.3   77     8  16            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 109    59      51  6.3   79     8  17            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 110    23     115  7.4   76     8  18            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 111    31     244 10.9   78     8  19            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 112    44     190 10.3   78     8  20            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 113    21     259 15.5   77     8  21            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 114     9      36 14.3   72     8  22            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 115    NA     255 12.6   75     8  23            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 116    45     212  9.7   79     8  24            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 117   168     238  3.4   81     8  25            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 118    73     215  8.0   86     8  26            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 119    NA     153  5.7   88     8  27            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 120    76     203  9.7   97     8  28            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 121   118     225  2.3   94     8  29            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 122    84     237  6.3   96     8  30            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 123    85     188  6.3   94     8  31            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 124    96     167  6.9   91     9   1            0.0</span>
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-<span class="r-out co"><span class="r-pr">#&gt;</span> 126    73     183  2.8   93     9   3            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 127    91     189  4.6   93     9   4            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 128    47      95  7.4   87     9   5            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 129    32      92 15.5   84     9   6            0.0</span>
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-<span class="r-out co"><span class="r-pr">#&gt;</span> 131    23     220 10.3   78     9   8            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 132    21     230 10.9   75     9   9            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 133    24     259  9.7   73     9  10            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 134    44     236 14.9   81     9  11            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 135    21     259 15.5   76     9  12            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 136    28     238  6.3   77     9  13            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 137     9      24 10.9   71     9  14            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 138    13     112 11.5   71     9  15            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 139    46     237  6.9   78     9  16            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 140    18     224 13.8   67     9  17            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 141    13      27 10.3   76     9  18            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 142    24     238 10.3   68     9  19            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 143    16     201  8.0   82     9  20            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 144    13     238 12.6   64     9  21            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 145    23      14  9.2   71     9  22            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 146    36     139 10.3   81     9  23            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 147     7      49 10.3   69     9  24            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 148    14      20 16.6   63     9  25            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 149    30     193  6.9   70     9  26            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 150    NA     145 13.2   77     9  27            0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 151    14     191 14.3   75     9  28            0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 152    18     131  8.0   76     9  29            0.0</span>
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-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu">add_prop_miss</span><span class="op">(</span><span class="va">Solar.R</span>, <span class="va">Ozone</span>, label <span class="op">=</span> <span class="st">"testing"</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>     Ozone Solar.R Wind Temp Month Day testing_vars</span>
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-<span class="r-out co"><span class="r-pr">#&gt;</span> 2      36     118  8.0   72     5   2          0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 3      12     149 12.6   74     5   3          0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 4      18     313 11.5   62     5   4          0.0</span>
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-<span class="r-out co"><span class="r-pr">#&gt;</span> 58     NA      47 10.3   73     6  27          0.5</span>
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-<span class="r-out co"><span class="r-pr">#&gt;</span> 93     39      83  6.9   81     8   1          0.0</span>
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-<span class="r-out co"><span class="r-pr">#&gt;</span> 95     16      77  7.4   82     8   3          0.0</span>
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-<span class="r-out co"><span class="r-pr">#&gt;</span> 97     35      NA  7.4   85     8   5          0.5</span>
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-<span class="r-out co"><span class="r-pr">#&gt;</span> 99    122     255  4.0   89     8   7          0.0</span>
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-<span class="r-out co"><span class="r-pr">#&gt;</span> 102    NA     222  8.6   92     8  10          0.5</span>
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-<span class="r-out co"><span class="r-pr">#&gt;</span> 115    NA     255 12.6   75     8  23          0.5</span>
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-<span class="r-out co"><span class="r-pr">#&gt;</span> 119    NA     153  5.7   88     8  27          0.5</span>
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-<span class="r-out co"><span class="r-pr">#&gt;</span> 131    23     220 10.3   78     9   8          0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 132    21     230 10.9   75     9   9          0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 133    24     259  9.7   73     9  10          0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 134    44     236 14.9   81     9  11          0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 135    21     259 15.5   76     9  12          0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 136    28     238  6.3   77     9  13          0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 137     9      24 10.9   71     9  14          0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 138    13     112 11.5   71     9  15          0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 139    46     237  6.9   78     9  16          0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 140    18     224 13.8   67     9  17          0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 141    13      27 10.3   76     9  18          0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 142    24     238 10.3   68     9  19          0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 143    16     201  8.0   82     9  20          0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 144    13     238 12.6   64     9  21          0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 145    23      14  9.2   71     9  22          0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 146    36     139 10.3   81     9  23          0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 147     7      49 10.3   69     9  24          0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 148    14      20 16.6   63     9  25          0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 149    30     193  6.9   70     9  26          0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 150    NA     145 13.2   77     9  27          0.5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 151    14     191 14.3   75     9  28          0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 152    18     131  8.0   76     9  29          0.0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 153    20     223 11.5   68     9  30          0.0</span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># this can be applied to model the proportion of missing data</span></span></span>
-<span class="r-in"><span><span class="co"># as in Tierney et al \doi{10.1136/bmjopen-2014-007450}</span></span></span>
-<span class="r-in"><span><span class="co"># see "Modelling missingness" in vignette "Getting Started with naniar"</span></span></span>
-<span class="r-in"><span><span class="co"># for details</span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
-
-
-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
-</div>
-
-<div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
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-
diff --git a/docs/reference/add_shadow.html b/docs/reference/add_shadow.html
deleted file mode 100644
index 8730ad13..00000000
--- a/docs/reference/add_shadow.html
+++ /dev/null
@@ -1,154 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="As an alternative to bind_shadow(), you can add specific individual shadow
-columns to a dataset. These also respect the dplyr verbs
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-      <img src="../logo.png" class="logo" alt=""><h1>Add a shadow column to dataframe</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/add-cols.R" class="external-link"><code>R/add-cols.R</code></a></small>
-      <div class="d-none name"><code>add_shadow.Rd</code></div>
-    </div>
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-    <div class="ref-description section level2">
-    <p>As an alternative to <code><a href="bind_shadow.html">bind_shadow()</a></code>, you can add specific individual shadow
-columns to a dataset. These also respect the dplyr verbs
-<code>starts_with</code>, <code>contains</code>, <code>ends_with</code>, etc.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">add_shadow</span><span class="op">(</span><span class="va">data</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>data.frame</p></dd>
-
-
-<dt>...</dt>
-<dd><p>One or more unquoted variable names, separated by commas. These also
-respect the dplyr verbs <code>starts_with</code>, <code>contains</code>, <code>ends_with</code>, etc.</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>data.frame</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="bind_shadow.html">bind_shadow()</a></code> <code><a href="add_any_miss.html">add_any_miss()</a></code> <code><a href="add_label_missings.html">add_label_missings()</a></code> <code><a href="add_label_shadow.html">add_label_shadow()</a></code> <code><a href="add_miss_cluster.html">add_miss_cluster()</a></code> <code><a href="add_n_miss.html">add_n_miss()</a></code> <code><a href="add_prop_miss.html">add_prop_miss()</a></code> <code><a href="add_shadow_shift.html">add_shadow_shift()</a></code> <code><a href="cast_shadow.html">cast_shadow()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu">add_shadow</span><span class="op">(</span><span class="va">Ozone</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 7</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    Ozone Solar.R  Wind  Temp Month   Day Ozone_NA</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>    41     190   7.4    67     5     1 !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>    36     118   8      72     5     2 !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>    12     149  12.6    74     5     3 !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>    18     313  11.5    62     5     4 !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>    <span style="color: #BB0000;">NA</span>      <span style="color: #BB0000;">NA</span>  14.3    56     5     5 NA      </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>    28      <span style="color: #BB0000;">NA</span>  14.9    66     5     6 !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>    23     299   8.6    65     5     7 !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>    19      99  13.8    59     5     8 !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>     8      19  20.1    61     5     9 !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>    <span style="color: #BB0000;">NA</span>     194   8.6    69     5    10 NA      </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu">add_shadow</span><span class="op">(</span><span class="va">Ozone</span>, <span class="va">Solar.R</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 8</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    Ozone Solar.R  Wind  Temp Month   Day Ozone_NA Solar.R_NA</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>    41     190   7.4    67     5     1 !NA      !NA       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>    36     118   8      72     5     2 !NA      !NA       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>    12     149  12.6    74     5     3 !NA      !NA       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>    18     313  11.5    62     5     4 !NA      !NA       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>    <span style="color: #BB0000;">NA</span>      <span style="color: #BB0000;">NA</span>  14.3    56     5     5 NA       NA        </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>    28      <span style="color: #BB0000;">NA</span>  14.9    66     5     6 !NA      NA        </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>    23     299   8.6    65     5     7 !NA      !NA       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>    19      99  13.8    59     5     8 !NA      !NA       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>     8      19  20.1    61     5     9 !NA      !NA       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>    <span style="color: #BB0000;">NA</span>     194   8.6    69     5    10 NA       !NA       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/add_shadow_shift.html b/docs/reference/add_shadow_shift.html
deleted file mode 100644
index 152e7292..00000000
--- a/docs/reference/add_shadow_shift.html
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-    <p>Shadow shift missing values using only the selected variables in a dataset,
-by specifying variable names or use dplyr <code>vars</code> and dplyr verbs
-<code>starts_with</code>, <code>contains</code>, <code>ends_with</code>, etc.</p>
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-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">add_shadow_shift</span><span class="op">(</span><span class="va">data</span>, <span class="va">...</span>, suffix <span class="op">=</span> <span class="st">"shift"</span><span class="op">)</span></span></code></pre></div>
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-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>data.frame</p></dd>
-
-
-<dt>...</dt>
-<dd><p>One or more unquoted variable names separated by commas. These also
-respect the dplyr verbs <code>starts_with</code>, <code>contains</code>, <code>ends_with</code>, etc.</p></dd>
-
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-<dt>suffix</dt>
-<dd><p>suffix to add to variable, defaults to "shift"</p></dd>
-
-</dl></div>
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-    
-
-<p>data with the added variable shifted named as <code>var_suffix</code></p>
-
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-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu">add_shadow_shift</span><span class="op">(</span><span class="va">Ozone</span>, <span class="va">Solar.R</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 8</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    Ozone Solar.R  Wind  Temp Month   Day Ozone_shift Solar.R_shift</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>       <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>    41     190   7.4    67     5     1        41           190  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>    36     118   8      72     5     2        36           118  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>    12     149  12.6    74     5     3        12           149  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>    18     313  11.5    62     5     4        18           313  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>    <span style="color: #BB0000;">NA</span>      <span style="color: #BB0000;">NA</span>  14.3    56     5     5       -<span style="color: #BB0000;">19.7</span>         -<span style="color: #BB0000;">33.6</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>    28      <span style="color: #BB0000;">NA</span>  14.9    66     5     6        28           -<span style="color: #BB0000;">33.1</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>    23     299   8.6    65     5     7        23           299  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>    19      99  13.8    59     5     8        19            99  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>     8      19  20.1    61     5     9         8            19  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>    <span style="color: #BB0000;">NA</span>     194   8.6    69     5    10       -<span style="color: #BB0000;">18.5</span>         194  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/add_span_counter.html b/docs/reference/add_span_counter.html
deleted file mode 100644
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+++ /dev/null
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-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/utils.R" class="external-link"><code>R/utils.R</code></a></small>
-      <div class="d-none name"><code>add_span_counter.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Adds a variable, <code>span_counter</code> to a dataframe. Used internally to facilitate
-counting of missing values over a given span.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">add_span_counter</span><span class="op">(</span><span class="va">data</span>, <span class="va">span_size</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
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-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>data.frame</p></dd>
-
-
-<dt>span_size</dt>
-<dd><p>integer</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>data.frame with extra variable "span_counter".</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="co"># add_span_counter(pedestrian, span_size = 100)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/all-is-miss-complete.html b/docs/reference/all-is-miss-complete.html
deleted file mode 100644
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--- a/docs/reference/all-is-miss-complete.html
+++ /dev/null
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-      <img src="../logo.png" class="logo" alt=""><h1>Identify if all values are missing or complete</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/helpers.R" class="external-link"><code>R/helpers.R</code></a></small>
-      <div class="d-none name"><code>all-is-miss-complete.Rd</code></div>
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-    <div class="ref-description section level2">
-    <p>This is shorthand for <code>all(is.na(x))</code> and <code>all(!is.na(x))</code></p>
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-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">all_na</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">all_miss</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">all_complete</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
-<dd><p>an R object to be tested.</p></dd>
-
-</dl></div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">misses</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="cn">NA</span>, <span class="cn">NA</span>, <span class="cn">NA</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="va">complete</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">1</span>, <span class="fl">2</span>, <span class="fl">3</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="va">mixture</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="cn">NA</span>, <span class="fl">1</span>, <span class="cn">NA</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">all_na</span><span class="op">(</span><span class="va">misses</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] TRUE</span>
-<span class="r-in"><span><span class="fu">all_na</span><span class="op">(</span><span class="va">complete</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] FALSE</span>
-<span class="r-in"><span><span class="fu">all_na</span><span class="op">(</span><span class="va">mixture</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] FALSE</span>
-<span class="r-in"><span><span class="fu">all_complete</span><span class="op">(</span><span class="va">misses</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] FALSE</span>
-<span class="r-in"><span><span class="fu">all_complete</span><span class="op">(</span><span class="va">complete</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] TRUE</span>
-<span class="r-in"><span><span class="fu">all_complete</span><span class="op">(</span><span class="va">mixture</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] FALSE</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/all_row_complete.html b/docs/reference/all_row_complete.html
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-    <h1>Helper function to determine whether all rows are complete</h1>
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-    <div class="hidden name"><code>all_row_complete.Rd</code></div>
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-    <p>Helper function to determine whether all rows are complete</p>
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-    <pre class="usage"><span class='fu'>all_row_complete</span>(<span class='no'>x</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
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-    <tr>
-      <th>x</th>
-      <td><p>a vector</p></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>logical vector</p>
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diff --git a/docs/reference/all_row_miss.html b/docs/reference/all_row_miss.html
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-    <div class="hidden name"><code>all_row_miss.Rd</code></div>
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-    
-    <p>Helper function to determine whether all rows are missing</p>
-    
-    </div>
-
-    <pre class="usage"><span class='fu'>all_row_miss</span>(<span class='no'>x</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>x</th>
-      <td><p>a vector</p></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>logical vector</p>
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-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
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diff --git a/docs/reference/any-na.html b/docs/reference/any-na.html
deleted file mode 100644
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-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="It is useful to search for any instances of missing or complete values. There
-Are two functions that do this in naniar - any_miss and it's alias
-any_na. These bother under the hood call anyNA. any_complete is
-the complement to any_miss - it returns TRUE if there are any complete values."><title>Identify if there are any missing or complete values — any-na • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Identify if there are any missing or complete values — any-na"><meta property="og:description" content="It is useful to search for any instances of missing or complete values. There
-Are two functions that do this in naniar - any_miss and it's alias
-any_na. These bother under the hood call anyNA. any_complete is
-the complement to any_miss - it returns TRUE if there are any complete values."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-      <img src="../logo.png" class="logo" alt=""><h1>Identify if there are any missing or complete values</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/helpers.R" class="external-link"><code>R/helpers.R</code></a></small>
-      <div class="d-none name"><code>any-na.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>It is useful to search for any instances of missing or complete values. There
-Are two functions that do this in <code>naniar</code> - <code>any_miss</code> and it's alias
-<code>any_na</code>. These bother under the hood call <code>anyNA</code>. <code>any_complete</code> is
-the complement to <code>any_miss</code> - it returns TRUE if there are any complete values.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">any_na</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">any_miss</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">any_complete</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
-<dd><p>an R object to be tested</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="all-is-miss-complete.html">all_miss()</a></code> <a href="all-is-miss-complete.html">all_complete</a></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/NA.html" class="external-link">anyNA</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] TRUE</span>
-<span class="r-in"><span><span class="fu">any_na</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] TRUE</span>
-<span class="r-in"><span><span class="fu">any_miss</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] TRUE</span>
-<span class="r-in"><span><span class="fu">any_complete</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] TRUE</span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
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diff --git a/docs/reference/any_row_miss.html b/docs/reference/any_row_miss.html
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--- a/docs/reference/any_row_miss.html
+++ /dev/null
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-    <p>logical vector - TRUE if contains a variable with a column ending in "_NA"</p>
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-<span class='no'>df_shadow</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='bind_shadow.html'>bind_shadow</a></span>(<span class='no'>airquality</span>)
-
-<span class='fu'>are_shadow</span>(<span class='no'>df_shadow</span>)</div><div class='output co'>#&gt;  [1] FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE</div><div class='input'>
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-    <div class="hidden name"><code>as_shadow.data.frame.Rd</code></div>
-    </div>
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-    <p>Return a tibble in shadow matrix form, where the variables are the same but
-have a suffix _NA attached to distinguish them.</p>
-    </div>
-
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-<span class='fu'><a href='as_shadow.html'>as_shadow</a></span>(<span class='no'>data</span>, <span class='no'>...</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>dataframe</p></td>
-    </tr>
-    <tr>
-      <th>...</th>
-      <td><p>selected variables to use</p></td>
-    </tr>
-    </table>
-
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'>
-<span class='fu'><a href='as_shadow.html'>as_shadow</a></span>(<span class='no'>airquality</span>)</div><div class='output co'>#&gt; <span style='color: #555555;'># A tibble: 153 x 6</span><span>
-#&gt;    Ozone_NA Solar.R_NA Wind_NA Temp_NA Month_NA Day_NA
-#&gt;    </span><span style='color: #555555;font-style: italic;'>&lt;fct&gt;</span><span>    </span><span style='color: #555555;font-style: italic;'>&lt;fct&gt;</span><span>      </span><span style='color: #555555;font-style: italic;'>&lt;fct&gt;</span><span>   </span><span style='color: #555555;font-style: italic;'>&lt;fct&gt;</span><span>   </span><span style='color: #555555;font-style: italic;'>&lt;fct&gt;</span><span>    </span><span style='color: #555555;font-style: italic;'>&lt;fct&gt;</span><span> 
-#&gt; </span><span style='color: #555555;'> 1</span><span> !NA      !NA        !NA     !NA     !NA      !NA   
-#&gt; </span><span style='color: #555555;'> 2</span><span> !NA      !NA        !NA     !NA     !NA      !NA   
-#&gt; </span><span style='color: #555555;'> 3</span><span> !NA      !NA        !NA     !NA     !NA      !NA   
-#&gt; </span><span style='color: #555555;'> 4</span><span> !NA      !NA        !NA     !NA     !NA      !NA   
-#&gt; </span><span style='color: #555555;'> 5</span><span> NA       NA         !NA     !NA     !NA      !NA   
-#&gt; </span><span style='color: #555555;'> 6</span><span> !NA      NA         !NA     !NA     !NA      !NA   
-#&gt; </span><span style='color: #555555;'> 7</span><span> !NA      !NA        !NA     !NA     !NA      !NA   
-#&gt; </span><span style='color: #555555;'> 8</span><span> !NA      !NA        !NA     !NA     !NA      !NA   
-#&gt; </span><span style='color: #555555;'> 9</span><span> !NA      !NA        !NA     !NA     !NA      !NA   
-#&gt; </span><span style='color: #555555;'>10</span><span> NA       !NA        !NA     !NA     !NA      !NA   
-#&gt; </span><span style='color: #555555;'># … with 143 more rows</span><span></div><div class='input'>
-</div></span></pre>
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diff --git a/docs/reference/as_shadow.html b/docs/reference/as_shadow.html
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-have a suffix _NA attached to distinguish them."><title>Create shadows — as_shadow • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Create shadows — as_shadow"><meta property="og:description" content="Return a tibble in shadow matrix form, where the variables are the same but
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-      <img src="../logo.png" class="logo" alt=""><h1>Create shadows</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/shadows.R" class="external-link"><code>R/shadows.R</code></a></small>
-      <div class="d-none name"><code>as_shadow.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Return a tibble in shadow matrix form, where the variables are the same but
-have a suffix _NA attached to distinguish them.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">as_shadow</span><span class="op">(</span><span class="va">data</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>dataframe</p></dd>
-
-
-<dt>...</dt>
-<dd><p>selected variables to use</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>appended shadow with column names</p>
-    </div>
-    <div class="section level2">
-    <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
-    <p>Representing missing data structure is achieved using the shadow matrix,
-introduced in <a href="https://www.researchgate.net/publication/2758672_Missing_Data_in_Interactive_High-Dimensional_Data_Visualization" class="external-link">Swayne and Buja</a>. The shadow
-matrix is the same dimension as the data, and consists of binary indicators
-of missingness of data values, where missing is represented as "NA", and not
-missing is represented as "!NA". Although these may be represented as 1 and
-0, respectively.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">as_shadow</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 6</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    Ozone_NA Solar.R_NA Wind_NA Temp_NA Month_NA Day_NA</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span> </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> !NA      !NA        !NA     !NA     !NA      !NA   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> !NA      !NA        !NA     !NA     !NA      !NA   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> !NA      !NA        !NA     !NA     !NA      !NA   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> !NA      !NA        !NA     !NA     !NA      !NA   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> NA       NA         !NA     !NA     !NA      !NA   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> !NA      NA         !NA     !NA     !NA      !NA   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> !NA      !NA        !NA     !NA     !NA      !NA   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> !NA      !NA        !NA     !NA     !NA      !NA   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> !NA      !NA        !NA     !NA     !NA      !NA   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> NA       !NA        !NA     !NA     !NA      !NA   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-</code></pre></div>
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-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
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diff --git a/docs/reference/as_shadow_upset.html b/docs/reference/as_shadow_upset.html
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@@ -1,119 +0,0 @@
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-      <img src="../logo.png" class="logo" alt=""><h1>Convert data into shadow format for doing an upset plot</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/shadows.R" class="external-link"><code>R/shadows.R</code></a></small>
-      <div class="d-none name"><code>as_shadow_upset.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Upset plots are a way of visualising common sets, this function transforms
-the data into a format that feeds directly into an upset plot</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">as_shadow_upset</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>a data.frame</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>a data.frame</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="http://github.com/hms-dbmi/UpSetR" class="external-link">UpSetR</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu">as_shadow_upset</span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="https://rdrr.io/pkg/UpSetR/man/upset.html" class="external-link">upset</a></span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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diff --git a/docs/reference/bind_shadow.html b/docs/reference/bind_shadow.html
deleted file mode 100644
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--- a/docs/reference/bind_shadow.html
+++ /dev/null
@@ -1,174 +0,0 @@
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-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Bind a shadow dataframe to original data</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/shadows.R" class="external-link"><code>R/shadows.R</code></a></small>
-      <div class="d-none name"><code>bind_shadow.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Binding a shadow matrix to a regular dataframe helps visualise and work with
-missing data.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">bind_shadow</span><span class="op">(</span><span class="va">data</span>, only_miss <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>a dataframe</p></dd>
-
-
-<dt>only_miss</dt>
-<dd><p>logical - if FALSE (default) it will bind a dataframe with
-all of the variables duplicated with their shadow. Setting this to TRUE
-will bind variables only those variables that contain missing values.
-See the examples for more details.</p></dd>
-
-
-<dt>...</dt>
-<dd><p>extra options to pass to <code><a href="recode_shadow.html">recode_shadow()</a></code> - a work in progress.</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>data with the added variable shifted and the suffix <code>_NA</code></p>
-
-
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">bind_shadow</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 12</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    Ozone Solar.R  Wind  Temp Month   Day Ozone_NA Solar.R_NA Wind_NA Temp_NA</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>    41     190   7.4    67     5     1 !NA      !NA        !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>    36     118   8      72     5     2 !NA      !NA        !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>    12     149  12.6    74     5     3 !NA      !NA        !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>    18     313  11.5    62     5     4 !NA      !NA        !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>    <span style="color: #BB0000;">NA</span>      <span style="color: #BB0000;">NA</span>  14.3    56     5     5 NA       NA         !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>    28      <span style="color: #BB0000;">NA</span>  14.9    66     5     6 !NA      NA         !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>    23     299   8.6    65     5     7 !NA      !NA        !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>    19      99  13.8    59     5     8 !NA      !NA        !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>     8      19  20.1    61     5     9 !NA      !NA        !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>    <span style="color: #BB0000;">NA</span>     194   8.6    69     5    10 NA       !NA        !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 2 more variables: Month_NA &lt;fct&gt;, Day_NA &lt;fct&gt;</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># bind only the variables that contain missing values</span></span></span>
-<span class="r-in"><span><span class="fu">bind_shadow</span><span class="op">(</span><span class="va">airquality</span>, only_miss <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 8</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    Ozone Solar.R  Wind  Temp Month   Day Ozone_NA Solar.R_NA</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>    41     190   7.4    67     5     1 !NA      !NA       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>    36     118   8      72     5     2 !NA      !NA       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>    12     149  12.6    74     5     3 !NA      !NA       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>    18     313  11.5    62     5     4 !NA      !NA       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>    <span style="color: #BB0000;">NA</span>      <span style="color: #BB0000;">NA</span>  14.3    56     5     5 NA       NA        </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>    28      <span style="color: #BB0000;">NA</span>  14.9    66     5     6 !NA      NA        </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>    23     299   8.6    65     5     7 !NA      !NA       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>    19      99  13.8    59     5     8 !NA      !NA       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>     8      19  20.1    61     5     9 !NA      !NA       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>    <span style="color: #BB0000;">NA</span>     194   8.6    69     5    10 NA       !NA       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">aq_shadow</span> <span class="op">&lt;-</span> <span class="fu">bind_shadow</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="co"># explore missing data visually</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># using the bounded shadow to visualise Ozone according to whether Solar</span></span></span>
-<span class="r-in"><span><span class="co"># Radiation is missing or not.</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">aq_shadow</span>,</span></span>
-<span class="r-in"><span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Ozone</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span></span>
-<span class="r-in"><span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_histogram.html" class="external-link">geom_histogram</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span></span>
-<span class="r-in"><span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/facet_wrap.html" class="external-link">facet_wrap</a></span><span class="op">(</span><span class="op">~</span><span class="va">Solar.R_NA</span>,</span></span>
-<span class="r-in"><span>       ncol <span class="op">=</span> <span class="fl">1</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/brfss.html b/docs/reference/brfss.html
deleted file mode 100644
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-Data, 2009. — brfss • narnia</title>
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-    <div class="page-header">
-    <h1>The Behavioral Risk Factor Surveillance System (BRFSS) Survey
-Data, 2009.</h1>
-    </div>
-
-    
-    <p>The data is a subset of the 2009 survey from BRFSS, an ongoing
-data collection program designed to measure behavioral risk
-factors for the adult population (18 years of age or older) living
-in households.</p>
-    
-
-    <pre class="usage"><span class='fu'>data</span>(<span class='no'>brfss</span>)</pre>
-        
-    <h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
-
-    <p><a href='http://www.cdc.gov/BRFSS/technical_infodata/surveydata/2009.htm'>http://www.cdc.gov/BRFSS/technical_infodata/surveydata/2009.htm</a></p>
-    
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>Also see the codebook:
-<a href='http://ftp.cdc.gov/pub/data/brfss/codebook_09.rtf'>http://ftp.cdc.gov/pub/data/brfss/codebook_09.rtf</a></p>
-<p>Format: a data frame with 245 observations on the following 34
-variables.</p><dl class='dl-horizontal'>
-    <dt><code>SEX</code></dt><dd><p>A factor with levels <code>Male</code> <code>Female</code>.</p></dd>
-    <dt><code>AGE</code></dt><dd><p>A numeric vector from 7 to 97.</p></dd>
-    <dt><code>HISPANC2</code></dt><dd><p>A factor with levels <code>Yes</code> <code>No</code>
-corresponding to the question: are you Hispanic or Latino?</p></dd>
-    <dt><code>VETERAN2</code></dt><dd><p>A factor with levels <code>1</code> <code>2</code>
-<code>3</code> <code>4</code> <code>5</code>. The question for this variable is:
-Have you ever served on active duty in the United States Armed
-Forces, either in the regular military or in a National Guard or
-military reserve unit? Active duty does not include training for
-the Reserves or National Guard, but DOES include activation, for
-example, for the Persian Gulf War. And the labels are meaning: 1:
-Yes, now on active duty; 2: Yes, on active duty during the last 12
-months, but not now; 3: Yes, on active duty in the past, but not
-during the last 12 months; 4: No, training for Reserves or
-National Guard only; 5: No, never served in the military.</p></dd>
-    <dt><code>MARITAL</code></dt><dd><p>A factor with levels <code>Married</code>
-<code>Divorced</code> <code>Widowed</code> <code>Separated</code>
-<code>NeverMarried</code> <code>UnmarriedCouple</code>.</p></dd>
-    <dt><code>CHILDREN</code></dt><dd><p>A numeric vector giving the number of
-children less than 18 years of age in household.</p></dd>
-    <dt><code>EDUCA</code></dt><dd><p>A factor with the education levels <code>1</code>
-<code>2</code> <code>3</code> <code>4</code> <code>5</code> <code>6</code> as 1: Never attended
-school or only kindergarten; 2: Grades 1 through 8 (Elementary);
-3: Grades 9 through 11 (Some high school); 4: Grade 12 or GED
-(High school graduate); 5: College 1 year to 3 years (Some college
-or technical school); 6: College 4 years or more  (College
-graduate).</p></dd>
-    <dt><code>EMPLOY</code></dt><dd><p>A factor showing the employment
-status with levels <code>1</code> <code>2</code> <code>3</code> <code>4</code> <code>5</code>
-<code>7</code> <code>8</code>. The labels mean --  1: Employed for wages; 2:
-Self-employed; 3: Out of work for  more than 1 year; 4: Out of
-work for less that 1 year;  5: A homemaker; 6: A student; 7:
-Retired; 8: Unable to work.</p></dd>
-    <dt><code>INCOME2</code></dt><dd><p>The annual household income from all sources with levels <code>&lt;10k</code> <code>10-15k</code> <code>15-20k</code> <code>20-25k</code> <code>25-35k</code> <code>35-50k</code> <code>50-75k</code> <code>&gt;75k</code> <code>Dontknow</code> <code>Refused</code>.</p></dd> <dt><code>WEIGHT2</code></dt><dd><p>The weight without shoes in pounds.</p></dd>
-    <dt><code>HEIGHT3</code></dt><dd><p>The weight without shoes in inches.</p></dd>
-    <dt><code>PREGNANT</code></dt><dd><p>Whether pregnant now with two
-levels <code>Yes</code> and <code>No</code>.</p></dd>  <dt><code>GENHLTH</code></dt><dd><p>The
-answer to the question "in general your health is" with levels
-<code>Excellent</code> <code>VeryGood</code> <code>Good</code> <code>Fair</code>
-<code>Poor</code> <code>Refused</code>.</p></dd>
-    <dt><code>PHYSHLTH</code></dt><dd><p>The number of
-days during the last 30 days that the respondent's physical health
-was not good.  -7 is for "Don't know/Not sure", and -9 is for
-"Refused".</p></dd>
-    <dt><code>MENTHLTH</code></dt><dd><p>The number of days during the
-last 30 days that the respondent's mental health was not good.  -7
-is for "Don't know/Not sure", and -9 is for "Refused".</p></dd>
-    <dt><code>POORHLTH</code></dt><dd><p>The number of days during the last 30 days
-that poor physical or mental health keep the respondent from doing
-usual activities, such as self-care, work, or recreation. -7 is
-for "Don't know/Not sure", and -9 is for "Refused".</p></dd>
-    <dt><code>HLTHPLAN</code></dt><dd><p>Whether having any kind of health care
-coverage, including health insurance, prepaid plans such as HMOs,
-or government plans such as Medicare. The answer has two levels:
-<code>Yes</code> and <code>No</code>.</p></dd>
-    <dt><code>CAREGIVE</code></dt><dd><p>Whether
-providing any such care or assistance to a friend or family member
-during the past month, with levels <code>Yes</code> and <code>No</code>.</p></dd>
-    <dt><code>QLACTLM2</code></dt><dd><p>Whether being limited in any way in any
-activities because of physical, mental, or emotional problems,
-with levels  <code>Yes</code> and <code>No</code>.</p></dd>
-    <dt><code>DRNKANY4</code></dt><dd><p>Whether having had at least one drink of
-any alcoholic beverage such as beer, wine, a malt beverage or
-liquor during the past 30 days, with levels <code>Yes</code> and
-<code>No</code>.</p></dd>
-    <dt><code>ALCDAY4</code></dt><dd><p>The number of days during the
-past 30 days that the respondent had at least one drink of any
-alcoholic beverage. -7 is for "Don't know/Not sure", and -9 is
-for "Refused".</p></dd>
-    <dt><code>AVEDRNK2</code></dt><dd><p>The number of drinks on the
-average the respondent had on the days when he/she drank, during
-the past 30 days. -7 is for "Don't know/Not sure", and -9 is for
-"Refused".</p></dd>
-    <dt><code>SMOKE100</code></dt><dd><p>Whether having smoked at least
-100 cigarettes in the entire life, with levels <code>Yes</code> and
-<code>No</code>.</p></dd>
-    <dt><code>SMOKDAY2</code></dt><dd><p>The frequency of days now
-smoking, with levels <code>Everyday</code> <code>Somedays</code> and
-<code>NotAtAll</code>(not at all).</p></dd>
-    <dt><code>STOPSMK2</code></dt><dd><p>Whether
-having stopped smoking for  one day or longer during the past 12
-months because the respondent was trying to quit smoking, with
-levels <code>Yes</code> and <code>No</code>.</p></dd>
-    <dt><code>LASTSMK1</code></dt><dd><p>A factor
-with levels <code>3</code> <code>4</code> <code>5</code> <code>6</code> <code>7</code> <code>8</code>
-corresponding to the question: how long has it been since last
-smokeing cigarettes regularly? The labels mean: 3: Within the past
-6 months (3 months but less than 6 months ago); 4: Within the past
-year (6 months but less than 1 year ago); 5: Within the past 5
-years (1 year but less than 5 years ago); 6: Within the past 10
-years (5 years but less than 10 years ago); 7: 10 years or more;
-8: Never smoked regularly.</p></dd>
-    <dt><code>FRUIT</code></dt><dd><p>The number of
-fruit the respondent eat every year, not counting juice. -7 is for
-"Don't know/Not sure", and -9 is for "Refused".</p></dd>
-    <dt><code>GREENSAL</code></dt><dd><p>The number of servings of green   salad the
-respondent eat every year. -7 is for "Don't  know/Not sure",
-and -9 is for "Refused".</p></dd>
-    <dt><code>POTATOES</code></dt><dd><p>The number of
-servings of potatoes, not including french fries, fried potatoes,
-or potato chips, that the respondent eat every year. -7 is for
-"Don't know/Not sure", and -9 is for "Refused".</p></dd>
-    <dt><code>CARROTS</code></dt><dd><p>The number of carrots the respondent eat
-every year. -7 is for  "Don't know/Not sure", and -9 is for
-"Refused".</p></dd>
-    <dt><code>VEGETABL</code></dt><dd><p>The number of servings of
-vegetables   the respondent eat every year, not counting carrots,
-potatoes, or salad. -7 is for "Don't know/Not sure", and -9 is
-for "Refused".</p></dd>
-    <dt><code>FRUITJUI</code></dt><dd><p>The number of fruit juices
-such as orange, grapefruit, or tomato that the respondent drink
-every year. -7 is   for "Don't know/Not sure", and -9 is for
-"Refused".</p></dd>
-    <dt><code>BMI4</code></dt><dd><p>Body Mass Index (BMI). Computed by
-WEIGHT in Kilograms/(HEIGHT in Meters * HEIGHT3 in Meters).
-Missing if any of WEIGHT2 or HEIGHT3 is missing.</p></dd> </dl>
-    
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <p>library(MissingDataGUI)</p>
-    
-
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
-      
-      <li><a href="#source">Source</a></li>
-
-      <li><a href="#details">Details</a></li>
-
-      <li><a href="#see-also">See also</a></li>
-          </ul>
-
-  </div>
-</div>
-
-      <footer>
-      <div class="copyright">
-  <p>Developed by Nicholas Tierney, Di Cook, Miles McBain.</p>
-</div>
-
-<div class="pkgdown">
-  <p>Site built with <a href="http://hadley.github.io/pkgdown/">pkgdown</a>.</p>
-</div>
-
-      </footer>
-   </div>
-
-  </body>
-</html>
diff --git a/docs/reference/cast_shadow-1.png b/docs/reference/cast_shadow-1.png
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diff --git a/docs/reference/cast_shadow.html b/docs/reference/cast_shadow.html
deleted file mode 100644
index 24363a1d..00000000
--- a/docs/reference/cast_shadow.html
+++ /dev/null
@@ -1,165 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Casting a shadow shifted column performs the equivalent pattern to
-data %&amp;gt;% select(var) %&amp;gt;% shadow_shift(). This is a convenience function
-that makes it easy to perform certain visualisations, in line with the
-principle that the user should have a way to flexibly return data formats
-containing information about the missing data. It forms the base building
-block for the functions cast_shadow_shift, and cast_shadow_shift_label.
-It also respects the dplyr verbs starts_with, contains, ends_with, etc.
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-data %&amp;gt;% select(var) %&amp;gt;% shadow_shift(). This is a convenience function
-that makes it easy to perform certain visualisations, in line with the
-principle that the user should have a way to flexibly return data formats
-containing information about the missing data. It forms the base building
-block for the functions cast_shadow_shift, and cast_shadow_shift_label.
-It also respects the dplyr verbs starts_with, contains, ends_with, etc.
-to select variables."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Add a shadow column to a dataset</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/cast-shadows.R" class="external-link"><code>R/cast-shadows.R</code></a></small>
-      <div class="d-none name"><code>cast_shadow.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Casting a shadow shifted column performs the equivalent pattern to
-data %&gt;% select(var) %&gt;% shadow_shift(). This is a convenience function
-that makes it easy to perform certain visualisations, in line with the
-principle that the user should have a way to flexibly return data formats
-containing information about the missing data. It forms the base building
-block for the functions <code>cast_shadow_shift</code>, and <code>cast_shadow_shift_label</code>.
-It also respects the dplyr verbs <code>starts_with</code>, <code>contains</code>, <code>ends_with</code>, etc.
-to select variables.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">cast_shadow</span><span class="op">(</span><span class="va">data</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>data.frame</p></dd>
-
-
-<dt>...</dt>
-<dd><p>One or more unquoted variable names separated by commas. These
-respect the dplyr verbs <code>starts_with</code>, <code>contains</code>, <code>ends_with</code>, etc.</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>data with the added variable shifted and the suffix <code>_NA</code></p>
-
-
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="cast_shadow_shift.html">cast_shadow_shift()</a></code>, <code><a href="cast_shadow_shift_label.html">cast_shadow_shift_label()</a></code> <code><a href="bind_shadow.html">bind_shadow()</a></code> <code><a href="add_any_miss.html">add_any_miss()</a></code> <code><a href="add_label_missings.html">add_label_missings()</a></code> <code><a href="add_label_shadow.html">add_label_shadow()</a></code> <code><a href="add_miss_cluster.html">add_miss_cluster()</a></code> <code><a href="add_prop_miss.html">add_prop_miss()</a></code> <code><a href="add_shadow_shift.html">add_shadow_shift()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu">cast_shadow</span><span class="op">(</span><span class="va">Ozone</span>, <span class="va">Solar.R</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 4</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    Ozone Solar.R Ozone_NA Solar.R_NA</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>    41     190 !NA      !NA       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>    36     118 !NA      !NA       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>    12     149 !NA      !NA       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>    18     313 !NA      !NA       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>    <span style="color: #BB0000;">NA</span>      <span style="color: #BB0000;">NA</span> NA       NA        </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>    28      <span style="color: #BB0000;">NA</span> !NA      NA        </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>    23     299 !NA      !NA       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>    19      99 !NA      !NA       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>     8      19 !NA      !NA       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>    <span style="color: #BB0000;">NA</span>     194 NA       !NA       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://magrittr.tidyverse.org" class="external-link">magrittr</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="va">airquality</span>  <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu">cast_shadow</span><span class="op">(</span><span class="va">Ozone</span>,<span class="va">Solar.R</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Ozone</span>,</span></span>
-<span class="r-in"><span>             colour <span class="op">=</span> <span class="va">Solar.R_NA</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span></span>
-<span class="r-in"><span>        <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_density.html" class="external-link">geom_density</a></span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/cast_shadow_shift.html b/docs/reference/cast_shadow_shift.html
deleted file mode 100644
index d182c322..00000000
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-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Add a shadow and a shadow_shift column to a dataset</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/cast-shadows.R" class="external-link"><code>R/cast-shadows.R</code></a></small>
-      <div class="d-none name"><code>cast_shadow_shift.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Shift the values and add a shadow column.  It also respects the dplyr
-verbs <code>starts_with</code>, <code>contains</code>, <code>ends_with</code>, etc.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">cast_shadow_shift</span><span class="op">(</span><span class="va">data</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>data.frame</p></dd>
-
-
-<dt>...</dt>
-<dd><p>One or more unquoted variable names separated by commas. These
-respect the dplyr verbs <code>starts_with</code>, <code>contains</code>, <code>ends_with</code>, etc.</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>data.frame with the shadow and shadow_shift vars</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code>cast_shadow_shift()</code>, <code><a href="cast_shadow_shift_label.html">cast_shadow_shift_label()</a></code> <code><a href="bind_shadow.html">bind_shadow()</a></code> <code><a href="add_any_miss.html">add_any_miss()</a></code> <code><a href="add_label_missings.html">add_label_missings()</a></code> <code><a href="add_label_shadow.html">add_label_shadow()</a></code> <code><a href="add_miss_cluster.html">add_miss_cluster()</a></code> <code><a href="add_prop_miss.html">add_prop_miss()</a></code> <code><a href="add_shadow_shift.html">add_shadow_shift()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu">cast_shadow_shift</span><span class="op">(</span><span class="va">Ozone</span>,<span class="va">Temp</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 6</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    Ozone  Temp Ozone_NA Temp_NA Ozone_shift Temp_shift</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>    41    67 !NA      !NA            41           67</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>    36    72 !NA      !NA            36           72</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>    12    74 !NA      !NA            12           74</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>    18    62 !NA      !NA            18           62</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>    <span style="color: #BB0000;">NA</span>    56 NA       !NA           -<span style="color: #BB0000;">19.7</span>         56</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>    28    66 !NA      !NA            28           66</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>    23    65 !NA      !NA            23           65</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>    19    59 !NA      !NA            19           59</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>     8    61 !NA      !NA             8           61</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>    <span style="color: #BB0000;">NA</span>    69 NA       !NA           -<span style="color: #BB0000;">18.5</span>         69</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu">cast_shadow_shift</span><span class="op">(</span><span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://tidyselect.r-lib.org/reference/starts_with.html" class="external-link">contains</a></span><span class="op">(</span><span class="st">"o"</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>`fct_explicit_na()` was deprecated in forcats 1.0.0.</span>
-<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span style="color: #00BBBB;">ℹ</span> Please use `fct_na_value_to_level()` instead.</span>
-<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span style="color: #00BBBB;">ℹ</span> The deprecated feature was likely used in the <span style="color: #0000BB;">naniar</span> package.</span>
-<span class="r-wrn co"><span class="r-pr">#&gt;</span>   Please report the issue at <span style="color: #0000BB; font-style: italic;">&lt;https://github.com/njtierney/naniar/issues&gt;</span>.</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 12</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    Ozone Solar.R Month Ozone_NA Solar.R_NA Month_NA Ozone_shift Solar.R_shift</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>          <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>    41     190     5 !NA      !NA        !NA             41           190  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>    36     118     5 !NA      !NA        !NA             36           118  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>    12     149     5 !NA      !NA        !NA             12           149  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>    18     313     5 !NA      !NA        !NA             18           313  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>    <span style="color: #BB0000;">NA</span>      <span style="color: #BB0000;">NA</span>     5 NA       NA         !NA            -<span style="color: #BB0000;">19.7</span>         -<span style="color: #BB0000;">33.6</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>    28      <span style="color: #BB0000;">NA</span>     5 !NA      NA         !NA             28           -<span style="color: #BB0000;">33.1</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>    23     299     5 !NA      !NA        !NA             23           299  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>    19      99     5 !NA      !NA        !NA             19            99  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>     8      19     5 !NA      !NA        !NA              8            19  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>    <span style="color: #BB0000;">NA</span>     194     5 NA       !NA        !NA            -<span style="color: #BB0000;">18.5</span>         194  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 4 more variables: Month_shift &lt;int&gt;, Ozone_NA_shift &lt;fct&gt;,</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   Solar.R_NA_shift &lt;fct&gt;, Month_NA_shift &lt;fct&gt;</span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
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-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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@@ -1,145 +0,0 @@
-<!DOCTYPE html>
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-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Add a shadow column and a shadow shifted column to a dataset</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/cast-shadows.R" class="external-link"><code>R/cast-shadows.R</code></a></small>
-      <div class="d-none name"><code>cast_shadow_shift_label.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Shift the values, add shadow, add missing label</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">cast_shadow_shift_label</span><span class="op">(</span><span class="va">data</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>data.frame</p></dd>
-
-
-<dt>...</dt>
-<dd><p>One or more unquoted expressions separated by commas. These also
-respect the dplyr verbs "starts_with", "contains", "ends_with", etc.</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>data.frame with the shadow and shadow_shift vars, and missing labels</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="cast_shadow_shift.html">cast_shadow_shift()</a></code>, <code>cast_shadow_shift_label()</code> <code><a href="bind_shadow.html">bind_shadow()</a></code> <code><a href="add_any_miss.html">add_any_miss()</a></code> <code><a href="add_label_missings.html">add_label_missings()</a></code> <code><a href="add_label_shadow.html">add_label_shadow()</a></code> <code><a href="add_miss_cluster.html">add_miss_cluster()</a></code> <code><a href="add_prop_miss.html">add_prop_miss()</a></code> <code><a href="add_shadow_shift.html">add_shadow_shift()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu">cast_shadow_shift_label</span><span class="op">(</span><span class="va">Ozone</span>, <span class="va">Solar.R</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 7</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    Ozone Solar.R Ozone_NA Solar.R_NA Ozone_shift Solar.R_shift any_missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>            <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>      </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>    41     190 !NA      !NA               41           190   Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>    36     118 !NA      !NA               36           118   Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>    12     149 !NA      !NA               12           149   Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>    18     313 !NA      !NA               18           313   Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>    <span style="color: #BB0000;">NA</span>      <span style="color: #BB0000;">NA</span> NA       NA               -<span style="color: #BB0000;">19.7</span>         -<span style="color: #BB0000;">33.6</span> Missing    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>    28      <span style="color: #BB0000;">NA</span> !NA      NA                28           -<span style="color: #BB0000;">33.1</span> Missing    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>    23     299 !NA      !NA               23           299   Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>    19      99 !NA      !NA               19            99   Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>     8      19 !NA      !NA                8            19   Not Missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>    <span style="color: #BB0000;">NA</span>     194 NA       !NA              -<span style="color: #BB0000;">18.5</span>         194   Missing    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># replicate the plot generated by geom_miss_point()</span></span></span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu">cast_shadow_shift_label</span><span class="op">(</span><span class="va">Ozone</span>,<span class="va">Solar.R</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Ozone_shift</span>,</span></span>
-<span class="r-in"><span>             y <span class="op">=</span> <span class="va">Solar.R_shift</span>,</span></span>
-<span class="r-in"><span>             colour <span class="op">=</span> <span class="va">any_missing</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span></span>
-<span class="r-in"><span>        <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_point.html" class="external-link">geom_point</a></span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
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diff --git a/docs/reference/common_na_numbers.html b/docs/reference/common_na_numbers.html
deleted file mode 100644
index 260e1b93..00000000
--- a/docs/reference/common_na_numbers.html
+++ /dev/null
@@ -1,152 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="This vector contains common number values of NA (missing), which is aimed to
-be used inside naniar functions miss_scan_count() and
-replace_with_na(). The current list of numbers can be found by printing
-out common_na_numbers. It is a useful way to explore your data for
-possible missings, but I strongly warn against using this to replace NA
-values without very carefully looking at the incidence for each of the
-cases. Common NA strings are in the data object common_na_strings."><title>Common number values for NA — common_na_numbers • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Common number values for NA — common_na_numbers"><meta property="og:description" content="This vector contains common number values of NA (missing), which is aimed to
-be used inside naniar functions miss_scan_count() and
-replace_with_na(). The current list of numbers can be found by printing
-out common_na_numbers. It is a useful way to explore your data for
-possible missings, but I strongly warn against using this to replace NA
-values without very carefully looking at the incidence for each of the
-cases. Common NA strings are in the data object common_na_strings."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-    <a class="dropdown-item" href="../articles/replace-with-na.html">Replace with NA</a>
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-
-      <ul class="navbar-nav"><li class="nav-item">
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-    <span class="fab fa fab fa-github fa-lg"></span>
-     
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-</li>
-      </ul></div>
-
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-  </div>
-</nav><div class="container template-reference-topic">
-<div class="row">
-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Common number values for NA</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/data-common-na-numbers.R" class="external-link"><code>R/data-common-na-numbers.R</code></a></small>
-      <div class="d-none name"><code>common_na_numbers.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>This vector contains common number values of NA (missing), which is aimed to
-be used inside naniar functions <code><a href="miss_scan_count.html">miss_scan_count()</a></code> and
-<code><a href="replace_with_na.html">replace_with_na()</a></code>. The current list of numbers can be found by printing
-out <code>common_na_numbers</code>. It is a useful way to explore your data for
-possible missings, but I strongly warn against using this to replace NA
-values without very carefully looking at the incidence for each of the
-cases. Common NA strings are in the data object <code>common_na_strings</code>.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="va">common_na_numbers</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="format">Format<a class="anchor" aria-label="anchor" href="#format"></a></h2>
-    <p>An object of class <code>numeric</code> of length 8.</p>
-    </div>
-    <div class="section level2">
-    <h2 id="note">Note<a class="anchor" aria-label="anchor" href="#note"></a></h2>
-    <p>original discussion here <a href="https://github.com/njtierney/naniar/issues/168" class="external-link">https://github.com/njtierney/naniar/issues/168</a></p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">dat_ms</span> <span class="op">&lt;-</span> <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/tribble.html" class="external-link">tribble</a></span><span class="op">(</span><span class="op">~</span><span class="va">x</span>,  <span class="op">~</span><span class="va">y</span>,    <span class="op">~</span><span class="va">z</span>,</span></span>
-<span class="r-in"><span>                          <span class="fl">1</span>,   <span class="st">"A"</span>,   <span class="op">-</span><span class="fl">100</span>,</span></span>
-<span class="r-in"><span>                          <span class="fl">3</span>,   <span class="st">"N/A"</span>, <span class="op">-</span><span class="fl">99</span>,</span></span>
-<span class="r-in"><span>                          <span class="cn">NA</span>,  <span class="cn">NA</span>,    <span class="op">-</span><span class="fl">98</span>,</span></span>
-<span class="r-in"><span>                          <span class="op">-</span><span class="fl">99</span>, <span class="st">"E"</span>,   <span class="op">-</span><span class="fl">101</span>,</span></span>
-<span class="r-in"><span>                          <span class="op">-</span><span class="fl">98</span>, <span class="st">"F"</span>,   <span class="op">-</span><span class="fl">1</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu"><a href="miss_scan_count.html">miss_scan_count</a></span><span class="op">(</span><span class="va">dat_ms</span>, <span class="op">-</span><span class="fl">99</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 3 × 2</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   Variable     n</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> x            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> y            0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> z            1</span>
-<span class="r-in"><span><span class="fu"><a href="miss_scan_count.html">miss_scan_count</a></span><span class="op">(</span><span class="va">dat_ms</span>, <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"-99"</span>,<span class="st">"-98"</span>,<span class="st">"N/A"</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 3 × 2</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   Variable     n</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> x            2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> y            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> z            2</span>
-<span class="r-in"><span><span class="va">common_na_numbers</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1]    -9   -99  -999 -9999  9999    66    77    88</span>
-<span class="r-in"><span><span class="fu"><a href="miss_scan_count.html">miss_scan_count</a></span><span class="op">(</span><span class="va">dat_ms</span>, <span class="va">common_na_numbers</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 3 × 2</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   Variable     n</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> x            2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> y            0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> z            2</span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
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-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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diff --git a/docs/reference/common_na_strings.html b/docs/reference/common_na_strings.html
deleted file mode 100644
index ffd7e64f..00000000
--- a/docs/reference/common_na_strings.html
+++ /dev/null
@@ -1,173 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content='This vector contains common values of NA (missing), which is aimed to
-be used inside naniar functions miss_scan_count() and
-replace_with_na(). The current list of
-strings used can be found by printing out common_na_strings. It is a
-useful way to explore your data for possible missings, but I strongly warn
-against using this to replace NA values without very carefully looking at
-the incidence for each of the cases. Please note that common_na_strings
-uses \\ around the "?", "." and "*" characters to protect against using
-their wildcard features in grep. Common NA numbers are in the data object
-common_na_numbers.'><title>Common string values for NA — common_na_strings • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Common string values for NA — common_na_strings"><meta property="og:description" content='This vector contains common values of NA (missing), which is aimed to
-be used inside naniar functions miss_scan_count() and
-replace_with_na(). The current list of
-strings used can be found by printing out common_na_strings. It is a
-useful way to explore your data for possible missings, but I strongly warn
-against using this to replace NA values without very carefully looking at
-the incidence for each of the cases. Please note that common_na_strings
-uses \\ around the "?", "." and "*" characters to protect against using
-their wildcard features in grep. Common NA numbers are in the data object
-common_na_numbers.'><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Common string values for NA</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/data-common-na-strings.R" class="external-link"><code>R/data-common-na-strings.R</code></a></small>
-      <div class="d-none name"><code>common_na_strings.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>This vector contains common values of NA (missing), which is aimed to
-be used inside naniar functions <code><a href="miss_scan_count.html">miss_scan_count()</a></code> and
-<code><a href="replace_with_na.html">replace_with_na()</a></code>. The current list of
-strings used can be found by printing out <code>common_na_strings</code>. It is a
-useful way to explore your data for possible missings, but I strongly warn
-against using this to replace NA values without very carefully looking at
-the incidence for each of the cases. Please note that <code>common_na_strings</code>
-uses <code>\\</code> around the "?", "." and "*" characters to protect against using
-their wildcard features in grep. Common NA numbers are in the data object
-<code>common_na_numbers</code>.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="va">common_na_strings</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="format">Format<a class="anchor" aria-label="anchor" href="#format"></a></h2>
-    <p>An object of class <code>character</code> of length 26.</p>
-    </div>
-    <div class="section level2">
-    <h2 id="note">Note<a class="anchor" aria-label="anchor" href="#note"></a></h2>
-    <p>original discussion here <a href="https://github.com/njtierney/naniar/issues/168" class="external-link">https://github.com/njtierney/naniar/issues/168</a></p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">dat_ms</span> <span class="op">&lt;-</span> <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/tribble.html" class="external-link">tribble</a></span><span class="op">(</span><span class="op">~</span><span class="va">x</span>,  <span class="op">~</span><span class="va">y</span>,    <span class="op">~</span><span class="va">z</span>,</span></span>
-<span class="r-in"><span>                          <span class="fl">1</span>,   <span class="st">"A"</span>,   <span class="op">-</span><span class="fl">100</span>,</span></span>
-<span class="r-in"><span>                          <span class="fl">3</span>,   <span class="st">"N/A"</span>, <span class="op">-</span><span class="fl">99</span>,</span></span>
-<span class="r-in"><span>                          <span class="cn">NA</span>,  <span class="cn">NA</span>,    <span class="op">-</span><span class="fl">98</span>,</span></span>
-<span class="r-in"><span>                          <span class="op">-</span><span class="fl">99</span>, <span class="st">"E"</span>,   <span class="op">-</span><span class="fl">101</span>,</span></span>
-<span class="r-in"><span>                          <span class="op">-</span><span class="fl">98</span>, <span class="st">"F"</span>,   <span class="op">-</span><span class="fl">1</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu"><a href="miss_scan_count.html">miss_scan_count</a></span><span class="op">(</span><span class="va">dat_ms</span>, <span class="op">-</span><span class="fl">99</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 3 × 2</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   Variable     n</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> x            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> y            0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> z            1</span>
-<span class="r-in"><span><span class="fu"><a href="miss_scan_count.html">miss_scan_count</a></span><span class="op">(</span><span class="va">dat_ms</span>, <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"-99"</span>,<span class="st">"-98"</span>,<span class="st">"N/A"</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 3 × 2</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   Variable     n</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> x            2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> y            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> z            2</span>
-<span class="r-in"><span><span class="va">common_na_strings</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [1] "missing" "NA"      "N A"     "N/A"     "#N/A"    "NA "     " NA"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [8] "N /A"    "N / A"   " N / A"  "N / A "  "na"      "n a"     "n/a"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [15] "na "     " na"     "n /a"    "n / a"   " a / a"  "n / a "  "NULL"   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [22] "null"    ""        "\\?"     "\\*"     "\\."    </span>
-<span class="r-in"><span><span class="fu"><a href="miss_scan_count.html">miss_scan_count</a></span><span class="op">(</span><span class="va">dat_ms</span>, <span class="va">common_na_strings</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 3 × 2</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   Variable     n</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> x            4</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> y            4</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> z            5</span>
-<span class="r-in"><span><span class="fu"><a href="replace_with_na.html">replace_with_na</a></span><span class="op">(</span><span class="va">dat_ms</span>, replace <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>y <span class="op">=</span> <span class="va">common_na_strings</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 5 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>       x y         z</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span>     1 A      -<span style="color: #BB0000;">100</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span>     3 <span style="color: #BB0000;">NA</span>      -<span style="color: #BB0000;">99</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span>    <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span>      -<span style="color: #BB0000;">98</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span>   -<span style="color: #BB0000;">99</span> E      -<span style="color: #BB0000;">101</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span>   -<span style="color: #BB0000;">98</span> F        -<span style="color: #BB0000;">1</span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
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-    <footer><div class="pkgdown-footer-left">
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diff --git a/docs/reference/draw_key.html b/docs/reference/draw_key.html
deleted file mode 100644
index 32cfafe0..00000000
--- a/docs/reference/draw_key.html
+++ /dev/null
@@ -1,115 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Each Geom has an associated function that draws the key when the geom needs
-to be displayed in a legend. These are the options built into naniar."><title>Key drawing functions — draw_key • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Key drawing functions — draw_key"><meta property="og:description" content="Each Geom has an associated function that draws the key when the geom needs
-to be displayed in a legend. These are the options built into naniar."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
-<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
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-<![endif]--></head><body>
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-    
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-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Key drawing functions</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/legend-draw.R" class="external-link"><code>R/legend-draw.R</code></a></small>
-      <div class="d-none name"><code>draw_key.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Each Geom has an associated function that draws the key when the geom needs
-to be displayed in a legend. These are the options built into naniar.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">draw_key_missing_point</span><span class="op">(</span><span class="va">data</span>, <span class="va">params</span>, <span class="va">size</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>A single row data frame containing the scaled aesthetics to
-display in this key</p></dd>
-
-
-<dt>params</dt>
-<dd><p>A list of additional parameters supplied to the geom.</p></dd>
-
-
-<dt>size</dt>
-<dd><p>Width and height of key in mm.</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A grid grob.</p>
-    </div>
-
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
-
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-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
-</div>
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diff --git a/docs/reference/figures/README-facet-by-month-1.png b/docs/reference/figures/README-facet-by-month-1.png
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diff --git a/docs/reference/gather_shadow.html b/docs/reference/gather_shadow.html
deleted file mode 100644
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+++ /dev/null
@@ -1,130 +0,0 @@
-<!DOCTYPE html>
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-missing contains the missing value representation."><title>Long form representation of a shadow matrix — gather_shadow • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Long form representation of a shadow matrix — gather_shadow"><meta property="og:description" content="gather_shadow is a long-form representation of binding the shadow matrix to
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-      <img src="../logo.png" class="logo" alt=""><h1>Long form representation of a shadow matrix</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/shadows.R" class="external-link"><code>R/shadows.R</code></a></small>
-      <div class="d-none name"><code>gather_shadow.Rd</code></div>
-    </div>
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-    <div class="ref-description section level2">
-    <p><code>gather_shadow</code> is a long-form representation of binding the shadow matrix to
-your data, producing variables named <code>case</code>, <code>variable</code>, and <code>missing</code>, where
-<code>missing</code> contains the missing value representation.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">gather_shadow</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>a dataframe</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>dataframe in long, format, containing information about the missings</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">gather_shadow</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 918 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>     case variable   missing</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>     1 Ozone_NA   !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>     1 Solar.R_NA !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>     1 Wind_NA    !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>     1 Temp_NA    !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>     1 Month_NA   !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>     1 Day_NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>     2 Ozone_NA   !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>     2 Solar.R_NA !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>     2 Wind_NA    !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>     2 Temp_NA    !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 908 more rows</span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
-
-
-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
-</div>
-
-<div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
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diff --git a/docs/reference/geom_miss_point.html b/docs/reference/geom_miss_point.html
deleted file mode 100644
index e8c7e53c..00000000
--- a/docs/reference/geom_miss_point.html
+++ /dev/null
@@ -1,215 +0,0 @@
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-data points 10\
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-<div class="row">
-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>geom_miss_point</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/geom-miss-point.R" class="external-link"><code>R/geom-miss-point.R</code></a></small>
-      <div class="d-none name"><code>geom_miss_point.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p><code>geom_miss_point</code> provides a way to transform and plot missing
-values in ggplot2. To do so it uses methods from ggobi to display missing
-data points 10\<!-- % below the minimum value, so that the values can be seen on -->
-the same axis.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">geom_miss_point</span><span class="op">(</span></span>
-<span>  mapping <span class="op">=</span> <span class="cn">NULL</span>,</span>
-<span>  data <span class="op">=</span> <span class="cn">NULL</span>,</span>
-<span>  prop_below <span class="op">=</span> <span class="fl">0.1</span>,</span>
-<span>  jitter <span class="op">=</span> <span class="fl">0.05</span>,</span>
-<span>  stat <span class="op">=</span> <span class="st">"miss_point"</span>,</span>
-<span>  position <span class="op">=</span> <span class="st">"identity"</span>,</span>
-<span>  colour <span class="op">=</span> <span class="va">..missing..</span>,</span>
-<span>  na.rm <span class="op">=</span> <span class="cn">FALSE</span>,</span>
-<span>  show.legend <span class="op">=</span> <span class="cn">NA</span>,</span>
-<span>  inherit.aes <span class="op">=</span> <span class="cn">TRUE</span>,</span>
-<span>  <span class="va">...</span></span>
-<span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>mapping</dt>
-<dd><p>Set of aesthetic mappings created by <code><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">ggplot2::aes()</a></code>
-or <code><a href="https://ggplot2.tidyverse.org/reference/aes_.html" class="external-link">ggplot2::aes_()</a></code>. If specified and <code>inherit.aes = TRUE</code>
-(the default), is combined with the default mapping at the top level of the
-plot. You only need to supply mapping if there isn't a mapping defined for
-the plot.</p></dd>
-
-
-<dt>data</dt>
-<dd><p>A data frame. If specified, overrides the default data frame
-defined at the top level of the plot.</p></dd>
-
-
-<dt>prop_below</dt>
-<dd><p>the degree to shift the values. The default is 0.1</p></dd>
-
-
-<dt>jitter</dt>
-<dd><p>the amount of jitter to add. The default is 0.05</p></dd>
-
-
-<dt>stat</dt>
-<dd><p>The statistical transformation to use on the data for this layer, as a string.</p></dd>
-
-
-<dt>position</dt>
-<dd><p>Position adjustment, either as a string, or the result of a
-call to a position adjustment function.</p></dd>
-
-
-<dt>colour</dt>
-<dd><p>the colour chosen for the aesthetic</p></dd>
-
-
-<dt>na.rm</dt>
-<dd><p>If <code>FALSE</code> (the default), removes missing values with a
-warning. If <code>TRUE</code> silently removes missing values.</p></dd>
-
-
-<dt>show.legend</dt>
-<dd><p>logical. Should this layer be included in the legends?
-<code>NA</code>, the default, includes if any aesthetics are mapped. <code>FALSE</code>
-never includes, and <code>TRUE</code> always includes.</p></dd>
-
-
-<dt>inherit.aes</dt>
-<dd><p>If <code>FALSE</code>, overrides the default aesthetics, rather
-than combining with them. This is most useful for helper functions that
-define both data and aesthetics and shouldn't inherit behaviour from the
-default plot specification, e.g. borders.</p></dd>
-
-
-<dt>...</dt>
-<dd><p>other arguments passed on to <code><a href="https://ggplot2.tidyverse.org/reference/layer.html" class="external-link">ggplot2::layer()</a></code>. There
-are three types of arguments you can use here:</p><ul><li><p>Aesthetics: to set an aesthetic to a fixed value, like
-<code>color = "red"</code> or <code>size = 3.</code></p></li>
-<li><p>Other arguments to the layer, for example you override the default
-<code>stat</code> associated with the layer.</p></li>
-<li><p>Other arguments passed on to the stat.</p></li>
-</ul></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
-    <p>Plot Missing Data Points</p>
-    </div>
-    <div class="section level2">
-    <h2 id="note">Note<a class="anchor" aria-label="anchor" href="#note"></a></h2>
-    <p>Warning message if na.rm = T is supplied.</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p>[gg_miss_case()][gg_miss_case_cumsum()][gg_miss_fct()][gg_miss_span()][gg_miss_var()][gg_miss_var_cumsum()][gg_miss_which()]</p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># using regular geom_point()</span></span></span>
-<span class="r-in"><span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">airquality</span>,</span></span>
-<span class="r-in"><span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Ozone</span>,</span></span>
-<span class="r-in"><span>           y <span class="op">=</span> <span class="va">Solar.R</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span></span>
-<span class="r-in"><span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_point.html" class="external-link">geom_point</a></span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># using  geom_miss_point()</span></span></span>
-<span class="r-in"><span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">airquality</span>,</span></span>
-<span class="r-in"><span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Ozone</span>,</span></span>
-<span class="r-in"><span>           y <span class="op">=</span> <span class="va">Solar.R</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span></span>
-<span class="r-in"><span> <span class="fu">geom_miss_point</span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span> <span class="co"># using facets</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">airquality</span>,</span></span>
-<span class="r-in"><span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Ozone</span>,</span></span>
-<span class="r-in"><span>           y <span class="op">=</span> <span class="va">Solar.R</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span></span>
-<span class="r-in"><span> <span class="fu">geom_miss_point</span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span></span>
-<span class="r-in"><span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/facet_wrap.html" class="external-link">facet_wrap</a></span><span class="op">(</span><span class="op">~</span><span class="va">Month</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/geom_missing_point-3.png b/docs/reference/geom_missing_point-3.png
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diff --git a/docs/reference/geom_missing_point.html b/docs/reference/geom_missing_point.html
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-    <div class="page-header">
-    <h1>geom_missing_point</h1>
-    </div>
-
-    
-    <p>Plot Missing Data Points</p>
-    
-
-    <pre class="usage"><span class='fu'>geom_missing_point</span>(<span class='kw'>mapping</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>data</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>position</span> <span class='kw'>=</span> <span class='st'>"identity"</span>,
-  <span class='kw'>colour</span> <span class='kw'>=</span> <span class='no'>..missing..</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='kw'>show.legend</span> <span class='kw'>=</span> <span class='fl'>NA</span>,
-  <span class='kw'>inherit.aes</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='no'>...</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a> Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>mapping</th>
-      <td><p>Set of aesthetic mappings created by <code><a href='http://www.rdocumentation.org/packages/ggplot2/topics/aes'>aes</a></code>
-or <code><a href='http://www.rdocumentation.org/packages/ggplot2/topics/aes_'>aes_</a></code>. If specified and <code>inherit.aes = TRUE</code>
-(the default), is combined with the default mapping at the top level of the
-plot. You only need to supply mapping if there isn't a mapping defined for
-the plot.</p></td>
-    </tr>
-    <tr>
-      <th>data</th>
-      <td><p>A data frame. If specified, overrides the default data frame
-defined at the top level of the plot.</p></td>
-    </tr>
-    <tr>
-      <th>position</th>
-      <td><p>Position adjustment, either as a string, or the result of a
-call to a position adjustment function.</p></td>
-    </tr>
-    <tr>
-      <th>colour</th>
-      <td><p>the colour chosen for the aesthetic</p></td>
-    </tr>
-    <tr>
-      <th>na.rm</th>
-      <td><p>If <code>FALSE</code> (the default), removes missing values with a
-warning. If <code>TRUE</code> silently removes missing values.</p></td>
-    </tr>
-    <tr>
-      <th>show.legend</th>
-      <td><p>logical. Should this layer be included in the legends?
-<code>NA</code>, the default, includes if any aesthetics are mapped. <code>FALSE</code>
-never includes, and <code>TRUE</code> always includes.</p></td>
-    </tr>
-    <tr>
-      <th>inherit.aes</th>
-      <td><p>If <code>FALSE</code>, overrides the default aesthetics, rather
-than combining with them. This is most useful for helper functions that
-define both data and aesthetics and shouldn't inherit behaviour from the
-default plot specification, e.g. borders.</p></td>
-    </tr>
-    <tr>
-      <th>...</th>
-      <td><p>other arguments passed on to <code><a href='http://www.rdocumentation.org/packages/ggplot2/topics/layer'>layer</a></code>. There
-are three types of arguments you can use here:</p><ul>
-<li><p>Aesthetics: to set an aesthetic to a fixed value, like
- <code>color = "red"</code> or <code>size = 3.</code></p></li>
-<li><p>Other arguments to the layer, for example you override the default
- <code>stat</code> associated with the layer.</p></li>
-<li><p>Other arguments passed on to the stat.</p></li>
-</ul></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p><code>geom_missing_point</code> adds a missing data point geometry to ggplot2. This displays missing data points 10<!-- % below the minimum value. --></p>
-    
-    <h2 class="hasAnchor" id="note"><a class="anchor" href="#note"></a>Note</h2>
-
-    <p>Warning message if na.rm = T is supplied.</p>
-    
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'>
-<span class='fu'>library</span>(<span class='no'>ggplot2</span>)
-
-<span class='co'># using regular geom_point()</span>
-<span class='fu'><a href='http://www.rdocumentation.org/packages/ggplot2/topics/ggplot'>ggplot</a></span>(<span class='no'>airquality</span>,
-       <span class='fu'><a href='http://www.rdocumentation.org/packages/ggplot2/topics/aes'>aes</a></span>(<span class='kw'>x</span> <span class='kw'>=</span> <span class='no'>Ozone</span>,
-           <span class='kw'>y</span> <span class='kw'>=</span> <span class='no'>Solar.R</span>)) +
-<span class='fu'><a href='http://www.rdocumentation.org/packages/ggplot2/topics/geom_point'>geom_point</a></span>()</div><div class='output co'>#&gt; <span class='warning'>Warning: Removed 42 rows containing missing values (geom_point).</span></div><img src='geom_missing_point-3.png' alt='' width='540' height='400' /><div class='input'>
-<span class='co'># using geom_missing_point()</span>
-<span class='fu'><a href='http://www.rdocumentation.org/packages/ggplot2/topics/ggplot'>ggplot</a></span>(<span class='no'>airquality</span>,
-       <span class='fu'><a href='http://www.rdocumentation.org/packages/ggplot2/topics/aes'>aes</a></span>(<span class='kw'>x</span> <span class='kw'>=</span> <span class='no'>Ozone</span>,
-           <span class='kw'>y</span> <span class='kw'>=</span> <span class='no'>Solar.R</span>)) +
-<span class='fu'>geom_missing_point</span>()</div><img src='geom_missing_point-5.png' alt='' width='540' height='400' /><div class='input'>
-</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
-      <li><a href="#arguments">Arguments</a></li>
-      
-      <li><a href="#details">Details</a></li>
-
-      <li><a href="#note">Note</a></li>
-      
-      <li><a href="#examples">Examples</a></li>
-    </ul>
-
-  </div>
-</div>
-
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-      <div class="copyright">
-  <p>Developed by Nicholas Tierney, Di Cook, Miles McBain.</p>
-</div>
-
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diff --git a/docs/reference/gg_miss_case.html b/docs/reference/gg_miss_case.html
deleted file mode 100644
index f6cd2378..00000000
--- a/docs/reference/gg_miss_case.html
+++ /dev/null
@@ -1,142 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="This is a visual analogue to miss_case_summary. It draws a ggplot of the
-number of missings in each case (row). A default minimal theme is used, which
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-number of missings in each case (row). A default minimal theme is used, which
-can be customised as normal for ggplot."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Plot the number of missings per case (row)</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/gg-miss-case.R" class="external-link"><code>R/gg-miss-case.R</code></a></small>
-      <div class="d-none name"><code>gg_miss_case.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>This is a visual analogue to <code>miss_case_summary</code>. It draws a ggplot of the
-number of missings in each case (row). A default minimal theme is used, which
-can be customised as normal for ggplot.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">gg_miss_case</span><span class="op">(</span><span class="va">x</span>, <span class="va">facet</span>, order_cases <span class="op">=</span> <span class="cn">TRUE</span>, show_pct <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
-<dd><p>data.frame</p></dd>
-
-
-<dt>facet</dt>
-<dd><p>(optional) a single bare variable name, if you want to create a faceted plot.</p></dd>
-
-
-<dt>order_cases</dt>
-<dd><p>logical Order the rows by missingness (default is FALSE -
-no order).</p></dd>
-
-
-<dt>show_pct</dt>
-<dd><p>logical Show the percentage of cases</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>a ggplot object depicting the number of missings in a given case.</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="geom_miss_point.html">geom_miss_point()</a></code> <a href="gg_miss_case_cumsum.html">gg_miss_case_cumsum</a> <code><a href="gg_miss_fct.html">gg_miss_fct()</a></code> <code><a href="gg_miss_span.html">gg_miss_span()</a></code> <code><a href="gg_miss_var.html">gg_miss_var()</a></code> <code><a href="gg_miss_var_cumsum.html">gg_miss_var_cumsum()</a></code> <code><a href="gg_miss_which.html">gg_miss_which()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">gg_miss_case</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-plt img"><img src="gg_miss_case-1.png" alt="" width="700" height="433"></span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="fu">gg_miss_case</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span> <span class="op">+</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span>x <span class="op">=</span> <span class="st">"Number of Cases"</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="fu">gg_miss_case</span><span class="op">(</span><span class="va">airquality</span>, show_pct <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="fu">gg_miss_case</span><span class="op">(</span><span class="va">airquality</span>, order_cases <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="fu">gg_miss_case</span><span class="op">(</span><span class="va">airquality</span>, facet <span class="op">=</span> <span class="va">Month</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="fu">gg_miss_case</span><span class="op">(</span><span class="va">airquality</span>, facet <span class="op">=</span> <span class="va">Month</span>, order_cases <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="fu">gg_miss_case</span><span class="op">(</span><span class="va">airquality</span>, facet <span class="op">=</span> <span class="va">Month</span>, show_pct <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
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-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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diff --git a/docs/reference/gg_miss_case_cumsum-1.png b/docs/reference/gg_miss_case_cumsum-1.png
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diff --git a/docs/reference/gg_miss_case_cumsum.html b/docs/reference/gg_miss_case_cumsum.html
deleted file mode 100644
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+++ /dev/null
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-<!DOCTYPE html>
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-      <img src="../logo.png" class="logo" alt=""><h1>Plot of cumulative sum of missing for cases</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/gg-miss-case-cumsum.R" class="external-link"><code>R/gg-miss-case-cumsum.R</code></a></small>
-      <div class="d-none name"><code>gg_miss_case_cumsum.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>A plot showing the cumulative sum of missing values for cases, reading the
-rows from the top to bottom. A default minimal theme is used, which can be
-customised as normal for ggplot.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">gg_miss_case_cumsum</span><span class="op">(</span><span class="va">x</span>, breaks <span class="op">=</span> <span class="fl">20</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
-<dd><p>a dataframe</p></dd>
-
-
-<dt>breaks</dt>
-<dd><p>the breaks for the x axis default is 20</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>a ggplot object depicting the number of missings</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="geom_miss_point.html">geom_miss_point()</a></code> <code><a href="gg_miss_case.html">gg_miss_case()</a></code> <code><a href="gg_miss_fct.html">gg_miss_fct()</a></code> <code><a href="gg_miss_span.html">gg_miss_span()</a></code> <code><a href="gg_miss_var.html">gg_miss_var()</a></code> <code><a href="gg_miss_var_cumsum.html">gg_miss_var_cumsum()</a></code> <code><a href="gg_miss_which.html">gg_miss_which()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">gg_miss_case_cumsum</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-plt img"><img src="gg_miss_case_cumsum-1.png" alt="" width="700" height="433"></span>
-</code></pre></div>
-    </div>
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-    </nav></aside></div>
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-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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diff --git a/docs/reference/gg_miss_fct.html b/docs/reference/gg_miss_fct.html
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-broken down by a categorical variable from the dataset. A default minimal
-theme is used, which can be customised as normal for ggplot."><title>Plot the number of missings for each variable, broken down by a factor — gg_miss_fct • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot the number of missings for each variable, broken down by a factor — gg_miss_fct"><meta property="og:description" content="This function draws a ggplot plot of the number of missings in each column,
-broken down by a categorical variable from the dataset. A default minimal
-theme is used, which can be customised as normal for ggplot."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Plot the number of missings for each variable, broken down by a factor</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/gg-miss-fct.R" class="external-link"><code>R/gg-miss-fct.R</code></a></small>
-      <div class="d-none name"><code>gg_miss_fct.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>This function draws a ggplot plot of the number of missings in each column,
-broken down by a categorical variable from the dataset. A default minimal
-theme is used, which can be customised as normal for ggplot.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">gg_miss_fct</span><span class="op">(</span><span class="va">x</span>, <span class="va">fct</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
-<dd><p>data.frame</p></dd>
-
-
-<dt>fct</dt>
-<dd><p>column containing the factor variable to visualise</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>ggplot object depicting the % missing of each factor level for
-each variable.</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="geom_miss_point.html">geom_miss_point()</a></code> <code><a href="gg_miss_case.html">gg_miss_case()</a></code> <a href="gg_miss_case_cumsum.html">gg_miss_case_cumsum</a> <code><a href="gg_miss_span.html">gg_miss_span()</a></code> <code><a href="gg_miss_var.html">gg_miss_var()</a></code> <code><a href="gg_miss_var_cumsum.html">gg_miss_var_cumsum()</a></code> <code><a href="gg_miss_which.html">gg_miss_which()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">gg_miss_fct</span><span class="op">(</span>x <span class="op">=</span> <span class="va">riskfactors</span>, fct <span class="op">=</span> <span class="va">marital</span><span class="op">)</span></span></span>
-<span class="r-plt img"><img src="gg_miss_fct-1.png" alt="" width="700" height="433"></span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="fu">gg_miss_fct</span><span class="op">(</span>x <span class="op">=</span> <span class="va">riskfactors</span>, fct <span class="op">=</span> <span class="va">marital</span><span class="op">)</span> <span class="op">+</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span>title <span class="op">=</span> <span class="st">"NA in Risk Factors and Marital status"</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
-
-
-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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diff --git a/docs/reference/gg_miss_span.html b/docs/reference/gg_miss_span.html
deleted file mode 100644
index 1bb3106f..00000000
--- a/docs/reference/gg_miss_span.html
+++ /dev/null
@@ -1,158 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="gg_miss_span is a replacement function to
-imputeTS::plotNA.distributionBar(tsNH4, breaksize = 100), which shows the
-number of missings in a given span, or breaksize. A default minimal theme
-is used, which can be customised as normal for ggplot."><title>Plot the number of missings in a given repeating span — gg_miss_span • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot the number of missings in a given repeating span — gg_miss_span"><meta property="og:description" content="gg_miss_span is a replacement function to
-imputeTS::plotNA.distributionBar(tsNH4, breaksize = 100), which shows the
-number of missings in a given span, or breaksize. A default minimal theme
-is used, which can be customised as normal for ggplot."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-<div class="row">
-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Plot the number of missings in a given repeating span</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/gg-miss-span.R" class="external-link"><code>R/gg-miss-span.R</code></a></small>
-      <div class="d-none name"><code>gg_miss_span.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p><code>gg_miss_span</code> is a replacement function to
-<code>imputeTS::plotNA.distributionBar(tsNH4, breaksize = 100)</code>, which shows the
-number of missings in a given span, or breaksize. A default minimal theme
-is used, which can be customised as normal for ggplot.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">gg_miss_span</span><span class="op">(</span><span class="va">data</span>, <span class="va">var</span>, <span class="va">span_every</span>, <span class="va">facet</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>data.frame</p></dd>
-
-
-<dt>var</dt>
-<dd><p>a bare unquoted variable name from <code>data</code>.</p></dd>
-
-
-<dt>span_every</dt>
-<dd><p>integer describing the length of the span to be explored</p></dd>
-
-
-<dt>facet</dt>
-<dd><p>(optional) a single bare variable name, if you want to create a faceted plot.</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>ggplot2 showing the number of missings in a span (window, or breaksize)</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="geom_miss_point.html">geom_miss_point()</a></code> <code><a href="gg_miss_case.html">gg_miss_case()</a></code> <a href="gg_miss_case_cumsum.html">gg_miss_case_cumsum</a> <code><a href="gg_miss_fct.html">gg_miss_fct()</a></code> <code><a href="gg_miss_var.html">gg_miss_var()</a></code> <code><a href="gg_miss_var_cumsum.html">gg_miss_var_cumsum()</a></code> <code><a href="gg_miss_which.html">gg_miss_which()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu"><a href="miss_var_span.html">miss_var_span</a></span><span class="op">(</span><span class="va">pedestrian</span>, <span class="va">hourly_counts</span>, span_every <span class="op">=</span> <span class="fl">3000</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 13 × 6</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    span_counter n_miss n_complete prop_miss prop_complete n_in_span</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>           <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>            1      0       <span style="text-decoration: underline;">3</span>000  0                1          <span style="text-decoration: underline;">3</span>000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>            2      0       <span style="text-decoration: underline;">3</span>000  0                1          <span style="text-decoration: underline;">3</span>000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>            3      1       <span style="text-decoration: underline;">2</span>999  0.000<span style="text-decoration: underline;">333</span>         1.00       <span style="text-decoration: underline;">3</span>000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>            4    121       <span style="text-decoration: underline;">2</span>879  0.040<span style="text-decoration: underline;">3</span>           0.960      <span style="text-decoration: underline;">3</span>000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>            5    503       <span style="text-decoration: underline;">2</span>497  0.168            0.832      <span style="text-decoration: underline;">3</span>000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>            6    555       <span style="text-decoration: underline;">2</span>445  0.185            0.815      <span style="text-decoration: underline;">3</span>000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>            7    190       <span style="text-decoration: underline;">2</span>810  0.063<span style="text-decoration: underline;">3</span>           0.937      <span style="text-decoration: underline;">3</span>000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>            8      0       <span style="text-decoration: underline;">3</span>000  0                1          <span style="text-decoration: underline;">3</span>000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>            9      1       <span style="text-decoration: underline;">2</span>999  0.000<span style="text-decoration: underline;">333</span>         1.00       <span style="text-decoration: underline;">3</span>000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>           10      0       <span style="text-decoration: underline;">3</span>000  0                1          <span style="text-decoration: underline;">3</span>000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">11</span>           11      0       <span style="text-decoration: underline;">3</span>000  0                1          <span style="text-decoration: underline;">3</span>000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">12</span>           12    745       <span style="text-decoration: underline;">2</span>255  0.248            0.752      <span style="text-decoration: underline;">3</span>000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">13</span>           13    432       <span style="text-decoration: underline;">1</span>268  0.254            0.746      <span style="text-decoration: underline;">1</span>700</span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="fu">gg_miss_span</span><span class="op">(</span><span class="va">pedestrian</span>, <span class="va">hourly_counts</span>, span_every <span class="op">=</span> <span class="fl">3000</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="fu">gg_miss_span</span><span class="op">(</span><span class="va">pedestrian</span>, <span class="va">hourly_counts</span>, span_every <span class="op">=</span> <span class="fl">3000</span>, facet <span class="op">=</span> <span class="va">sensor_name</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="co"># works with the rest of ggplot</span></span></span>
-<span class="r-in"><span><span class="fu">gg_miss_span</span><span class="op">(</span><span class="va">pedestrian</span>, <span class="va">hourly_counts</span>, span_every <span class="op">=</span> <span class="fl">3000</span><span class="op">)</span> <span class="op">+</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span>x <span class="op">=</span> <span class="st">"custom"</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="fu">gg_miss_span</span><span class="op">(</span><span class="va">pedestrian</span>, <span class="va">hourly_counts</span>, span_every <span class="op">=</span> <span class="fl">3000</span><span class="op">)</span> <span class="op">+</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_dark</a></span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
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-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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diff --git a/docs/reference/gg_miss_upset.html b/docs/reference/gg_miss_upset.html
deleted file mode 100644
index 52932b08..00000000
--- a/docs/reference/gg_miss_upset.html
+++ /dev/null
@@ -1,149 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Upset plots are a way of visualising common sets, gg_miss_upset shows the
-number of missing values for each of the sets of data. The default option
-of gg_miss_upset is taken from UpSetR::upset - which is to use up to 5
-sets and up to 40 interactions. We also set the ordering to by the
-frequency of the intersections. Setting nsets = 5 means to look at 5
-variables and their combinations. The number of combinations or rather
-intersections is controlled by nintersects. If there are 40
-intersections, there will be 40 combinations of variables explored. The
-number of sets and intersections can be changed by passing arguments nsets = 10 to look at 10 sets of variables, and nintersects = 50 to look at 50
-intersections."><title>Plot the pattern of missingness using an upset plot. — gg_miss_upset • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot the pattern of missingness using an upset plot. — gg_miss_upset"><meta property="og:description" content="Upset plots are a way of visualising common sets, gg_miss_upset shows the
-number of missing values for each of the sets of data. The default option
-of gg_miss_upset is taken from UpSetR::upset - which is to use up to 5
-sets and up to 40 interactions. We also set the ordering to by the
-frequency of the intersections. Setting nsets = 5 means to look at 5
-variables and their combinations. The number of combinations or rather
-intersections is controlled by nintersects. If there are 40
-intersections, there will be 40 combinations of variables explored. The
-number of sets and intersections can be changed by passing arguments nsets = 10 to look at 10 sets of variables, and nintersects = 50 to look at 50
-intersections."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-      <img src="../logo.png" class="logo" alt=""><h1>Plot the pattern of missingness using an upset plot.</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/gg-miss-upset.R" class="external-link"><code>R/gg-miss-upset.R</code></a></small>
-      <div class="d-none name"><code>gg_miss_upset.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Upset plots are a way of visualising common sets, <code>gg_miss_upset</code> shows the
-number of missing values for each of the sets of data. The default option
-of <code>gg_miss_upset</code> is taken from <code><a href="https://rdrr.io/pkg/UpSetR/man/upset.html" class="external-link">UpSetR::upset</a></code> - which is to use up to 5
-sets and up to 40 interactions. We also set the ordering to by the
-frequency of the intersections. Setting <code>nsets = 5</code> means to look at 5
-variables and their combinations. The number of combinations or rather
-<code>intersections</code> is controlled by <code>nintersects</code>. If there are 40
-intersections, there will be 40 combinations of variables explored. The
-number of sets and intersections can be changed by passing arguments <code>nsets = 10</code> to look at 10 sets of variables, and <code>nintersects = 50</code> to look at 50
-intersections.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">gg_miss_upset</span><span class="op">(</span><span class="va">data</span>, order.by <span class="op">=</span> <span class="st">"freq"</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>data.frame</p></dd>
-
-
-<dt>order.by</dt>
-<dd><p>(from UpSetR::upset) How the intersections in the matrix should be ordered by. Options include frequency (entered as "freq"), degree, or both in any order.  See <code><a href="https://rdrr.io/pkg/UpSetR/man/upset.html" class="external-link">?UpSetR::upset</a></code> for more options</p></dd>
-
-
-<dt>...</dt>
-<dd><p>arguments to pass to upset plot - see <code><a href="https://rdrr.io/pkg/UpSetR/man/upset.html" class="external-link">?UpSetR::upset</a></code></p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>a ggplot visualisation of missing data</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="fu">gg_miss_upset</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="fu">gg_miss_upset</span><span class="op">(</span><span class="va">riskfactors</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="fu">gg_miss_upset</span><span class="op">(</span><span class="va">riskfactors</span>, nsets <span class="op">=</span> <span class="fl">10</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="fu">gg_miss_upset</span><span class="op">(</span><span class="va">riskfactors</span>, nsets <span class="op">=</span> <span class="fl">10</span>, nintersects <span class="op">=</span> <span class="fl">10</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
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-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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diff --git a/docs/reference/gg_miss_var-1.png b/docs/reference/gg_miss_var-1.png
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diff --git a/docs/reference/gg_miss_var.html b/docs/reference/gg_miss_var.html
deleted file mode 100644
index c50750ca..00000000
--- a/docs/reference/gg_miss_var.html
+++ /dev/null
@@ -1,139 +0,0 @@
-<!DOCTYPE html>
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-number of missings in each variable, ordered to show which variables have
-the most missing data. A default minimal theme is used, which can be
-customised as normal for ggplot."><title>Plot the number of missings for each variable — gg_miss_var • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plot the number of missings for each variable — gg_miss_var"><meta property="og:description" content="This is a visual analogue to miss_var_summary. It draws a ggplot of the
-number of missings in each variable, ordered to show which variables have
-the most missing data. A default minimal theme is used, which can be
-customised as normal for ggplot."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-<div class="row">
-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Plot the number of missings for each variable</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/gg-miss-var.R" class="external-link"><code>R/gg-miss-var.R</code></a></small>
-      <div class="d-none name"><code>gg_miss_var.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>This is a visual analogue to <code>miss_var_summary</code>. It draws a ggplot of the
-number of missings in each variable, ordered to show which variables have
-the most missing data. A default minimal theme is used, which can be
-customised as normal for ggplot.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">gg_miss_var</span><span class="op">(</span><span class="va">x</span>, <span class="va">facet</span>, show_pct <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
-<dd><p>a dataframe</p></dd>
-
-
-<dt>facet</dt>
-<dd><p>(optional) bare variable name, if you want to create a faceted plot.</p></dd>
-
-
-<dt>show_pct</dt>
-<dd><p>logical shows the number of missings (default), but if set to
-TRUE, it will display the proportion of missings.</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>a ggplot object depicting the number of missings in a given column</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="geom_miss_point.html">geom_miss_point()</a></code> <code><a href="gg_miss_case.html">gg_miss_case()</a></code> <a href="gg_miss_case_cumsum.html">gg_miss_case_cumsum</a> <code><a href="gg_miss_fct.html">gg_miss_fct()</a></code> <code><a href="gg_miss_span.html">gg_miss_span()</a></code> <code>gg_miss_var()</code> <code><a href="gg_miss_var_cumsum.html">gg_miss_var_cumsum()</a></code> <code><a href="gg_miss_which.html">gg_miss_which()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">gg_miss_var</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-plt img"><img src="gg_miss_var-1.png" alt="" width="700" height="433"></span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="fu">gg_miss_var</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span> <span class="op">+</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span>y <span class="op">=</span> <span class="st">"Look at all the missing ones"</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="fu">gg_miss_var</span><span class="op">(</span><span class="va">airquality</span>, <span class="va">Month</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="fu">gg_miss_var</span><span class="op">(</span><span class="va">airquality</span>, <span class="va">Month</span>, show_pct <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="fu">gg_miss_var</span><span class="op">(</span><span class="va">airquality</span>, <span class="va">Month</span>, show_pct <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> <span class="op">+</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/lims.html" class="external-link">ylim</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">100</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
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-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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diff --git a/docs/reference/gg_miss_var_cumsum-1.png b/docs/reference/gg_miss_var_cumsum-1.png
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diff --git a/docs/reference/gg_miss_var_cumsum.html b/docs/reference/gg_miss_var_cumsum.html
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-reading columns from the left to the right of the initial dataframe. A
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-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Plot of cumulative sum of missing value for each variable</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/gg-miss-var-cumsum.R" class="external-link"><code>R/gg-miss-var-cumsum.R</code></a></small>
-      <div class="d-none name"><code>gg_miss_var_cumsum.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>A plot showing the cumulative sum of missing values for each variable,
-reading columns from the left to the right of the initial dataframe. A
-default minimal theme is used, which can be customised as normal for ggplot.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">gg_miss_var_cumsum</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
-<dd><p>a data.frame</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>a ggplot object showing the cumulative sum of missings over the variables</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="geom_miss_point.html">geom_miss_point()</a></code> <code><a href="gg_miss_case.html">gg_miss_case()</a></code> <a href="gg_miss_case_cumsum.html">gg_miss_case_cumsum</a> <code><a href="gg_miss_fct.html">gg_miss_fct()</a></code> <code><a href="gg_miss_span.html">gg_miss_span()</a></code> <code><a href="gg_miss_var.html">gg_miss_var()</a></code> <code><a href="gg_miss_which.html">gg_miss_which()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">gg_miss_var_cumsum</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-plt img"><img src="gg_miss_var_cumsum-1.png" alt="" width="700" height="433"></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
-
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-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
-</div>
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-<div class="pkgdown-footer-right">
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diff --git a/docs/reference/gg_miss_which.html b/docs/reference/gg_miss_which.html
deleted file mode 100644
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-      <img src="../logo.png" class="logo" alt=""><h1>Plot which variables contain a missing value</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/gg-miss-which.R" class="external-link"><code>R/gg-miss-which.R</code></a></small>
-      <div class="d-none name"><code>gg_miss_which.Rd</code></div>
-    </div>
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-    <div class="ref-description section level2">
-    <p>This plot produces a set of rectangles indicating whether there is a missing
-element in a column or not.  A default minimal theme is used, which can be
-customised as normal for ggplot.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">gg_miss_which</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
-<dd><p>a dataframe</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>a ggplot object of which variables contains missing values</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="geom_miss_point.html">geom_miss_point()</a></code> <code><a href="gg_miss_case.html">gg_miss_case()</a></code> <a href="gg_miss_case_cumsum.html">gg_miss_case_cumsum</a> <code><a href="gg_miss_fct.html">gg_miss_fct()</a></code> <code><a href="gg_miss_span.html">gg_miss_span()</a></code> <code><a href="gg_miss_var.html">gg_miss_var()</a></code> <code><a href="gg_miss_var_cumsum.html">gg_miss_var_cumsum()</a></code> <code>gg_miss_which()</code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">gg_miss_which</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-plt img"><img src="gg_miss_which-1.png" alt="" width="700" height="433"></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
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-
-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
-</div>
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-<div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
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diff --git a/docs/reference/gg_missing_case-2.png b/docs/reference/gg_missing_case-2.png
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diff --git a/docs/reference/gg_missing_case.html b/docs/reference/gg_missing_case.html
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-    <div class="page-header">
-    <h1>Plot the number of missings per case (row)</h1>
-    </div>
-
-    
-    <p>This function draws a ggplot of the number of missings in each row.
-At this point I'm not sure how this plot should be arranged, as it currently looks a bit ugly!</p>
-    
-
-    <pre class="usage"><span class='fu'>gg_missing_case</span>(<span class='no'>x</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a> Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>x</th>
-      <td><p>a dataframe</p></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>a ggplot plot depicting the number of missings in a given case</p>
-    
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'>
-<span class='fu'>gg_missing_case</span>(<span class='no'>airquality</span>)</div><img src='gg_missing_case-2.png' alt='' width='540' height='400' /><div class='input'>
-</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
-      <li><a href="#arguments">Arguments</a></li>
-      
-      <li><a href="#value">Value</a></li>
-      
-      <li><a href="#examples">Examples</a></li>
-    </ul>
-
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-  <p>Developed by Nicholas Tierney, Di Cook, Miles McBain.</p>
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diff --git a/docs/reference/gg_missing_var.html b/docs/reference/gg_missing_var.html
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-    <h1>Plot the number of missings for each variable</h1>
-    </div>
-
-    
-    <p>This function draws a ggplot plot of the number of missings in each column, rearranged to show which variables have the most missing data.</p>
-    
-
-    <pre class="usage"><span class='fu'>gg_missing_var</span>(<span class='no'>x</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a> Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>x</th>
-      <td><p>a dataframe</p></td>
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-    </table>
-    
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>a ggplot plot depicting the number of missings in a given column</p>
-    
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'>
-<span class='fu'>gg_missing_var</span>(<span class='no'>airquality</span>)</div><img src='gg_missing_var-2.png' alt='' width='540' height='400' /><div class='input'>
-</div></pre>
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-  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
-      <li><a href="#arguments">Arguments</a></li>
-      
-      <li><a href="#value">Value</a></li>
-      
-      <li><a href="#examples">Examples</a></li>
-    </ul>
-
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diff --git a/docs/reference/gg_missing_which.html b/docs/reference/gg_missing_which.html
deleted file mode 100644
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-    <h1>Plot which variables contain a missing value</h1>
-    </div>
-
-    
-    <p><code>gg_missing_which</code> (need a better name!) produces a set of rectangles that indicate whether there is a missing element in a column or not</p>
-    
-
-    <pre class="usage"><span class='fu'>gg_missing_which</span>(<span class='no'>x</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a> Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>x</th>
-      <td><p>a dataframe</p></td>
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-    </table>
-    
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>a ggplot plot</p>
-    
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'>
-<span class='fu'>gg_missing_which</span>(<span class='no'>airquality</span>)</div><img src='gg_missing_which-2.png' alt='' width='540' height='400' /><div class='input'>
-</div></pre>
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-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
-      <li><a href="#arguments">Arguments</a></li>
-      
-      <li><a href="#value">Value</a></li>
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diff --git a/docs/reference/group_by_fun.html b/docs/reference/group_by_fun.html
deleted file mode 100644
index c96a4c7c..00000000
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-    </div>
-
-    <pre class="usage"><span class='fu'>group_by_fun</span>(<span class='no'>data</span>, <span class='no'>.fun</span>, <span class='no'>...</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>data.frame, which will be grouped</p></td>
-    </tr>
-    <tr>
-      <th>.fun</th>
-      <td><p>a function to apply</p></td>
-    </tr>
-    <tr>
-      <th>...</th>
-      <td><p>additional arguments to be passed to map</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>a dataframe with the function applied to each group</p>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'>
-<span class='kw'>if</span> (<span class='fl'>FALSE</span>) {
-<span class='no'>miss_case_table.grouped_df</span> <span class='kw'>&lt;-</span> <span class='kw'>function</span>(<span class='no'>data</span>){
-<span class='fu'>group_by_fun</span>(<span class='no'>data</span>,<span class='kw'>.fun</span> <span class='kw'>=</span> <span class='no'>miss_case_table</span>)
-}
-<span class='no'>airquality</span> <span class='kw'>%&gt;%</span>
-<span class='fu'>group_by</span>(<span class='no'>Month</span>) <span class='kw'>%&gt;%</span>
-<span class='fu'><a href='miss_case_table.html'>miss_case_table</a></span>()
-}</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
-      <li><a href="#arguments">Arguments</a></li>
-      <li><a href="#value">Value</a></li>
-      <li><a href="#examples">Examples</a></li>
-    </ul>
-
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diff --git a/docs/reference/impute_below.html b/docs/reference/impute_below.html
deleted file mode 100644
index ec116b02..00000000
--- a/docs/reference/impute_below.html
+++ /dev/null
@@ -1,112 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="It can be useful in exploratory graphics to impute data outside the range of
-the data. impute_below imputes all variables with missings to have values
-10 percent below the range for numeric values, and for character or factor
-values adds a new string or label. It is powered by shadow_shift, so please
-see the documentation for shadow_shift() to full details on the different
-implementations."><title>Impute data with values shifted 10 percent below range. — impute_below • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Impute data with values shifted 10 percent below range. — impute_below"><meta property="og:description" content="It can be useful in exploratory graphics to impute data outside the range of
-the data. impute_below imputes all variables with missings to have values
-10 percent below the range for numeric values, and for character or factor
-values adds a new string or label. It is powered by shadow_shift, so please
-see the documentation for shadow_shift() to full details on the different
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-      <img src="../logo.png" class="logo" alt=""><h1>Impute data with values shifted 10 percent below range.</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/impute_below.R" class="external-link"><code>R/impute_below.R</code></a></small>
-      <div class="d-none name"><code>impute_below.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>It can be useful in exploratory graphics to impute data outside the range of
-the data. <code>impute_below</code> imputes all variables with missings to have values
-10 percent below the range for numeric values, and for character or factor
-values adds a new string or label. It is powered by <code>shadow_shift</code>, so please
-see the documentation for <code><a href="shadow_shift.html">shadow_shift()</a></code> to full details on the different
-implementations.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">impute_below</span><span class="op">(</span><span class="va">...</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>...</dt>
-<dd><p>extra arguments to pass - see <code><a href="shadow_shift.html">shadow_shift()</a></code> for discussion on this.</p></dd>
-
-</dl></div>
-
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diff --git a/docs/reference/impute_below_all.html b/docs/reference/impute_below_all.html
deleted file mode 100644
index 8e3bf0e8..00000000
--- a/docs/reference/impute_below_all.html
+++ /dev/null
@@ -1,326 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="It can be useful in exploratory graphics to impute data outside the range of
-the data. impute_below_all imputes all variables with missings to have
-values 10\
-values adds a new string or label."><title>Impute data with values shifted 10 percent below range. — impute_below_all • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Impute data with values shifted 10 percent below range. — impute_below_all"><meta property="og:description" content="It can be useful in exploratory graphics to impute data outside the range of
-the data. impute_below_all imputes all variables with missings to have
-values 10\
-values adds a new string or label."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Impute data with values shifted 10 percent below range.</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/impute_below.R" class="external-link"><code>R/impute_below.R</code></a></small>
-      <div class="d-none name"><code>impute_below_all.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>It can be useful in exploratory graphics to impute data outside the range of
-the data. <code>impute_below_all</code> imputes all variables with missings to have
-values 10\<!-- % below the range for numeric values, and for character or factor -->
-values adds a new string or label.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">impute_below_all</span><span class="op">(</span><span class="va">.tbl</span>, prop_below <span class="op">=</span> <span class="fl">0.1</span>, jitter <span class="op">=</span> <span class="fl">0.05</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>.tbl</dt>
-<dd><p>a data.frame</p></dd>
-
-
-<dt>prop_below</dt>
-<dd><p>the degree to shift the values. default is</p></dd>
-
-
-<dt>jitter</dt>
-<dd><p>the amount of jitter to add. default is 0.05</p></dd>
-
-
-<dt>...</dt>
-<dd><p>additional arguments</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>an dataset with values imputed</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># you can impute data like so:</span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu">impute_below_all</span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>         Ozone   Solar.R Wind Temp Month Day</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 1    41.00000 190.00000  7.4   67     5   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 2    36.00000 118.00000  8.0   72     5   2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 3    12.00000 149.00000 12.6   74     5   3</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 4    18.00000 313.00000 11.5   62     5   4</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 5   -19.72321 -33.57778 14.3   56     5   5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 6    28.00000 -33.07810 14.9   66     5   6</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 7    23.00000 299.00000  8.6   65     5   7</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 8    19.00000  99.00000 13.8   59     5   8</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 9     8.00000  19.00000 20.1   61     5   9</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 10  -18.51277 194.00000  8.6   69     5  10</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 11    7.00000 -21.37719  6.9   74     5  11</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 12   16.00000 256.00000  9.7   69     5  12</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 13   11.00000 290.00000  9.2   66     5  13</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 14   14.00000 274.00000 10.9   68     5  14</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 15   18.00000  65.00000 13.2   58     5  15</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 16   14.00000 334.00000 11.5   64     5  16</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 17   34.00000 307.00000 12.0   66     5  17</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 18    6.00000  78.00000 18.4   57     5  18</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 19   30.00000 322.00000 11.5   68     5  19</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 20   11.00000  44.00000  9.7   62     5  20</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 21    1.00000   8.00000  9.7   59     5  21</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 22   11.00000 320.00000 16.6   73     5  22</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 23    4.00000  25.00000  9.7   61     5  23</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 24   32.00000  92.00000 12.0   61     5  24</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 25  -17.81863  66.00000 16.6   57     5  25</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 26  -19.43853 266.00000 14.9   58     5  26</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 27  -15.14310 -24.60954  8.0   57     5  27</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 28   23.00000  13.00000 12.0   67     5  28</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 29   45.00000 252.00000 14.9   81     5  29</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 30  115.00000 223.00000  5.7   79     5  30</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 31   37.00000 279.00000  7.4   76     5  31</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 32  -16.17315 286.00000  8.6   78     6   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 33  -14.65883 287.00000  9.7   74     6   2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 34  -17.85609 242.00000 16.1   67     6   3</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 35  -13.29299 186.00000  9.2   84     6   4</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 36  -16.16323 220.00000  8.6   85     6   5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 37  -19.60935 264.00000 14.3   79     6   6</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 38   29.00000 127.00000  9.7   82     6   7</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 39  -19.65780 273.00000  6.9   87     6   8</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 40   71.00000 291.00000 13.8   90     6   9</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 41   39.00000 323.00000 11.5   87     6  10</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 42  -13.40961 259.00000 10.9   93     6  11</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 43  -13.53728 250.00000  9.2   92     6  12</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 44   23.00000 148.00000  8.0   82     6  13</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 45  -19.65993 332.00000 13.8   80     6  14</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 46  -16.48342 322.00000 11.5   79     6  15</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 47   21.00000 191.00000 14.9   77     6  16</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 48   37.00000 284.00000 20.7   72     6  17</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 49   20.00000  37.00000  9.2   65     6  18</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 50   12.00000 120.00000 11.5   73     6  19</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 51   13.00000 137.00000 10.3   76     6  20</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 52  -17.17718 150.00000  6.3   77     6  21</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 53  -16.74073  59.00000  1.7   76     6  22</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 54  -13.65786  91.00000  4.6   76     6  23</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 55  -16.78786 250.00000  6.3   76     6  24</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 56  -12.30098 135.00000  8.0   75     6  25</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 57  -13.33171 127.00000  8.0   78     6  26</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 58  -16.77414  47.00000 10.3   73     6  27</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 59  -17.08225  98.00000 11.5   80     6  28</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 60  -15.98818  31.00000 14.9   77     6  29</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 61  -19.17558 138.00000  8.0   83     6  30</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 62  135.00000 269.00000  4.1   84     7   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 63   49.00000 248.00000  9.2   85     7   2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 64   32.00000 236.00000  9.2   81     7   3</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 65  -14.27138 101.00000 10.9   84     7   4</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 66   64.00000 175.00000  4.6   83     7   5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 67   40.00000 314.00000 10.9   83     7   6</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 68   77.00000 276.00000  5.1   88     7   7</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 69   97.00000 267.00000  6.3   92     7   8</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 70   97.00000 272.00000  5.7   92     7   9</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 71   85.00000 175.00000  7.4   89     7  10</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 72  -13.51764 139.00000  8.6   82     7  11</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 73   10.00000 264.00000 14.3   73     7  12</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 74   27.00000 175.00000 14.9   81     7  13</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 75  -13.48998 291.00000 14.9   91     7  14</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 76    7.00000  48.00000 14.3   80     7  15</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 77   48.00000 260.00000  6.9   81     7  16</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 78   35.00000 274.00000 10.3   82     7  17</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 79   61.00000 285.00000  6.3   84     7  18</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 80   79.00000 187.00000  5.1   87     7  19</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 81   63.00000 220.00000 11.5   85     7  20</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 82   16.00000   7.00000  6.9   74     7  21</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 83  -16.92150 258.00000  9.7   81     7  22</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 84  -16.60335 295.00000 11.5   82     7  23</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 85   80.00000 294.00000  8.6   86     7  24</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 86  108.00000 223.00000  8.0   85     7  25</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 87   20.00000  81.00000  8.6   82     7  26</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 88   52.00000  82.00000 12.0   86     7  27</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 89   82.00000 213.00000  7.4   88     7  28</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 90   50.00000 275.00000  7.4   86     7  29</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 91   64.00000 253.00000  7.4   83     7  30</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 92   59.00000 254.00000  9.2   81     7  31</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 93   39.00000  83.00000  6.9   81     8   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 94    9.00000  24.00000 13.8   81     8   2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 95   16.00000  77.00000  7.4   82     8   3</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 96   78.00000 -30.94374  6.9   86     8   4</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 97   35.00000 -33.38707  7.4   85     8   5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 98   66.00000 -21.48980  4.6   87     8   6</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 99  122.00000 255.00000  4.0   89     8   7</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 100  89.00000 229.00000 10.3   90     8   8</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 101 110.00000 207.00000  8.0   90     8   9</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 102 -14.78907 222.00000  8.6   92     8  10</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 103 -16.19151 137.00000 11.5   86     8  11</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 104  44.00000 192.00000 11.5   86     8  12</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 105  28.00000 273.00000 11.5   82     8  13</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 106  65.00000 157.00000  9.7   80     8  14</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 107 -19.73591  64.00000 11.5   79     8  15</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 108  22.00000  71.00000 10.3   77     8  16</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 109  59.00000  51.00000  6.3   79     8  17</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 110  23.00000 115.00000  7.4   76     8  18</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 111  31.00000 244.00000 10.9   78     8  19</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 112  44.00000 190.00000 10.3   78     8  20</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 113  21.00000 259.00000 15.5   77     8  21</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 114   9.00000  36.00000 14.3   72     8  22</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 115 -18.92235 255.00000 12.6   75     8  23</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 116  45.00000 212.00000  9.7   79     8  24</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 117 168.00000 238.00000  3.4   81     8  25</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 118  73.00000 215.00000  8.0   86     8  26</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 119 -14.86296 153.00000  5.7   88     8  27</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 120  76.00000 203.00000  9.7   97     8  28</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 121 118.00000 225.00000  2.3   94     8  29</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 122  84.00000 237.00000  6.3   96     8  30</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 123  85.00000 188.00000  6.3   94     8  31</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 124  96.00000 167.00000  6.9   91     9   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 125  78.00000 197.00000  5.1   92     9   2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 126  73.00000 183.00000  2.8   93     9   3</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 127  91.00000 189.00000  4.6   93     9   4</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 128  47.00000  95.00000  7.4   87     9   5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 129  32.00000  92.00000 15.5   84     9   6</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 130  20.00000 252.00000 10.9   80     9   7</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 131  23.00000 220.00000 10.3   78     9   8</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 132  21.00000 230.00000 10.9   75     9   9</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 133  24.00000 259.00000  9.7   73     9  10</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 134  44.00000 236.00000 14.9   81     9  11</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 135  21.00000 259.00000 15.5   76     9  12</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 136  28.00000 238.00000  6.3   77     9  13</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 137   9.00000  24.00000 10.9   71     9  14</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 138  13.00000 112.00000 11.5   71     9  15</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 139  46.00000 237.00000  6.9   78     9  16</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 140  18.00000 224.00000 13.8   67     9  17</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 141  13.00000  27.00000 10.3   76     9  18</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 142  24.00000 238.00000 10.3   68     9  19</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 143  16.00000 201.00000  8.0   82     9  20</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 144  13.00000 238.00000 12.6   64     9  21</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 145  23.00000  14.00000  9.2   71     9  22</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 146  36.00000 139.00000 10.3   81     9  23</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 147   7.00000  49.00000 10.3   69     9  24</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 148  14.00000  20.00000 16.6   63     9  25</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 149  30.00000 193.00000  6.9   70     9  26</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 150 -14.83089 145.00000 13.2   77     9  27</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 151  14.00000 191.00000 14.3   75     9  28</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 152  18.00000 131.00000  8.0   76     9  29</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 153  20.00000 223.00000 11.5   68     9  30</span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># However, this does not show you WHERE the missing values are.</span></span></span>
-<span class="r-in"><span><span class="co"># to keep track of them, you want to use `bind_shadow()` first.</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="bind_shadow.html">bind_shadow</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu">impute_below_all</span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 12</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    Ozone Solar.R  Wind  Temp Month   Day Ozone_NA Solar.R_NA Wind_NA Temp_NA</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>  41     190     7.4    67     5     1 !NA      !NA        !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>  36     118     8      72     5     2 !NA      !NA        !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>  12     149    12.6    74     5     3 !NA      !NA        !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>  18     313    11.5    62     5     4 !NA      !NA        !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> -<span style="color: #BB0000;">19.7</span>   -<span style="color: #BB0000;">33.6</span>  14.3    56     5     5 NA       NA         !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>  28     -<span style="color: #BB0000;">33.1</span>  14.9    66     5     6 !NA      NA         !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>  23     299     8.6    65     5     7 !NA      !NA        !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>  19      99    13.8    59     5     8 !NA      !NA        !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>   8      19    20.1    61     5     9 !NA      !NA        !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> -<span style="color: #BB0000;">18.5</span>   194     8.6    69     5    10 NA       !NA        !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 2 more variables: Month_NA &lt;fct&gt;, Day_NA &lt;fct&gt;</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># This identifies where the missing values are located, which means you</span></span></span>
-<span class="r-in"><span><span class="co"># can do things like this:</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="bind_shadow.html">bind_shadow</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu">impute_below_all</span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="co"># identify where there are missings across rows.</span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="add_label_shadow.html">add_label_shadow</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Ozone</span>,</span></span>
-<span class="r-in"><span>             y <span class="op">=</span> <span class="va">Solar.R</span>,</span></span>
-<span class="r-in"><span>             colour <span class="op">=</span> <span class="va">any_missing</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_point.html" class="external-link">geom_point</a></span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="co"># Note that this ^^ is a long version of `geom_miss_point()`.</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
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-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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diff --git a/docs/reference/impute_below_at.html b/docs/reference/impute_below_at.html
deleted file mode 100644
index 04f53dd4..00000000
--- a/docs/reference/impute_below_at.html
+++ /dev/null
@@ -1,462 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="impute_below operates on all variables. To only impute variables
-that satisfy a specific condition, use the scoped variants,
-impute_below_at, and impute_below_if. To use _at effectively,
-you must know that _at`` affects variables selected with a character vector, or with vars()`."><title>Scoped variants of impute_below — impute_below_at • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Scoped variants of impute_below — impute_below_at"><meta property="og:description" content="impute_below operates on all variables. To only impute variables
-that satisfy a specific condition, use the scoped variants,
-impute_below_at, and impute_below_if. To use _at effectively,
-you must know that _at`` affects variables selected with a character vector, or with vars()`."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Scoped variants of <code>impute_below</code></h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/impute_below.R" class="external-link"><code>R/impute_below.R</code></a></small>
-      <div class="d-none name"><code>impute_below_at.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p><code>impute_below</code> operates on all variables. To only impute variables
-that satisfy a specific condition, use the scoped variants,
-<code>impute_below_at</code>, and <code>impute_below_if</code>. To use <code>_at</code> effectively,
-you must know that <code>_at`` affects variables selected with a character vector, or with </code>vars()`.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">impute_below_at</span><span class="op">(</span><span class="va">.tbl</span>, <span class="va">.vars</span>, prop_below <span class="op">=</span> <span class="fl">0.1</span>, jitter <span class="op">=</span> <span class="fl">0.05</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>.tbl</dt>
-<dd><p>a data.frame</p></dd>
-
-
-<dt>.vars</dt>
-<dd><p>variables to impute</p></dd>
-
-
-<dt>prop_below</dt>
-<dd><p>the degree to shift the values. default is</p></dd>
-
-
-<dt>jitter</dt>
-<dd><p>the amount of jitter to add. default is 0.05</p></dd>
-
-
-<dt>...</dt>
-<dd><p>extra arguments</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>an dataset with values imputed</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># select variables starting with a particular string.</span></span></span>
-<span class="r-in"><span><span class="fu">impute_below_at</span><span class="op">(</span><span class="va">airquality</span>,</span></span>
-<span class="r-in"><span>                .vars <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Ozone"</span>, <span class="st">"Solar.R"</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>         Ozone   Solar.R Wind Temp Month Day</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 1    41.00000 190.00000  7.4   67     5   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 2    36.00000 118.00000  8.0   72     5   2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 3    12.00000 149.00000 12.6   74     5   3</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 4    18.00000 313.00000 11.5   62     5   4</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 5   -19.72321 -33.57778 14.3   56     5   5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 6    28.00000 -33.07810 14.9   66     5   6</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 7    23.00000 299.00000  8.6   65     5   7</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 8    19.00000  99.00000 13.8   59     5   8</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 9     8.00000  19.00000 20.1   61     5   9</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 10  -18.51277 194.00000  8.6   69     5  10</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 11    7.00000 -21.37719  6.9   74     5  11</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 12   16.00000 256.00000  9.7   69     5  12</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 13   11.00000 290.00000  9.2   66     5  13</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 14   14.00000 274.00000 10.9   68     5  14</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 15   18.00000  65.00000 13.2   58     5  15</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 16   14.00000 334.00000 11.5   64     5  16</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 17   34.00000 307.00000 12.0   66     5  17</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 18    6.00000  78.00000 18.4   57     5  18</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 19   30.00000 322.00000 11.5   68     5  19</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 20   11.00000  44.00000  9.7   62     5  20</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 21    1.00000   8.00000  9.7   59     5  21</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 22   11.00000 320.00000 16.6   73     5  22</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 23    4.00000  25.00000  9.7   61     5  23</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 24   32.00000  92.00000 12.0   61     5  24</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 25  -17.81863  66.00000 16.6   57     5  25</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 26  -19.43853 266.00000 14.9   58     5  26</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 27  -15.14310 -24.60954  8.0   57     5  27</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 28   23.00000  13.00000 12.0   67     5  28</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 29   45.00000 252.00000 14.9   81     5  29</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 30  115.00000 223.00000  5.7   79     5  30</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 31   37.00000 279.00000  7.4   76     5  31</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 32  -16.17315 286.00000  8.6   78     6   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 33  -14.65883 287.00000  9.7   74     6   2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 34  -17.85609 242.00000 16.1   67     6   3</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 35  -13.29299 186.00000  9.2   84     6   4</span>
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-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="fu">impute_below_at</span><span class="op">(</span><span class="va">airquality</span>,</span></span>
-<span class="r-in"><span>                .vars <span class="op">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html" class="external-link">vars</a></span><span class="op">(</span><span class="va">Ozone</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="bind_shadow.html">bind_shadow</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu">impute_below_at</span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html" class="external-link">vars</a></span><span class="op">(</span><span class="va">Ozone</span>, <span class="va">Solar.R</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="add_label_shadow.html">add_label_shadow</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Ozone</span>,</span></span>
-<span class="r-in"><span>             y <span class="op">=</span> <span class="va">Solar.R</span>,</span></span>
-<span class="r-in"><span>             colour <span class="op">=</span> <span class="va">any_missing</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span></span>
-<span class="r-in"><span>         <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_point.html" class="external-link">geom_point</a></span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
-
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-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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diff --git a/docs/reference/impute_below_if.html b/docs/reference/impute_below_if.html
deleted file mode 100644
index af3c06b5..00000000
--- a/docs/reference/impute_below_if.html
+++ /dev/null
@@ -1,287 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="impute_below operates on all variables. To only impute variables
-that satisfy a specific condition, use the scoped variants,
-impute_below_at, and impute_below_if."><title>Scoped variants of impute_below — impute_below_if • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Scoped variants of impute_below — impute_below_if"><meta property="og:description" content="impute_below operates on all variables. To only impute variables
-that satisfy a specific condition, use the scoped variants,
-impute_below_at, and impute_below_if."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Scoped variants of <code>impute_below</code></h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/impute_below.R" class="external-link"><code>R/impute_below.R</code></a></small>
-      <div class="d-none name"><code>impute_below_if.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p><code>impute_below</code> operates on all variables. To only impute variables
-that satisfy a specific condition, use the scoped variants,
-<code>impute_below_at</code>, and <code>impute_below_if</code>.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">impute_below_if</span><span class="op">(</span><span class="va">.tbl</span>, <span class="va">.predicate</span>, prop_below <span class="op">=</span> <span class="fl">0.1</span>, jitter <span class="op">=</span> <span class="fl">0.05</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>.tbl</dt>
-<dd><p>data.frame</p></dd>
-
-
-<dt>.predicate</dt>
-<dd><p>A predicate function (such as is.numeric)</p></dd>
-
-
-<dt>prop_below</dt>
-<dd><p>the degree to shift the values. default is</p></dd>
-
-
-<dt>jitter</dt>
-<dd><p>the amount of jitter to add. default is 0.05</p></dd>
-
-
-<dt>...</dt>
-<dd><p>extra arguments</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>an dataset with values imputed</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu">impute_below_if</span><span class="op">(</span>.predicate <span class="op">=</span> <span class="va">is.numeric</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>         Ozone   Solar.R Wind Temp Month Day</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 1    41.00000 190.00000  7.4   67     5   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 2    36.00000 118.00000  8.0   72     5   2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 3    12.00000 149.00000 12.6   74     5   3</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 4    18.00000 313.00000 11.5   62     5   4</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 5   -19.72321 -33.57778 14.3   56     5   5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 6    28.00000 -33.07810 14.9   66     5   6</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 7    23.00000 299.00000  8.6   65     5   7</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 8    19.00000  99.00000 13.8   59     5   8</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 9     8.00000  19.00000 20.1   61     5   9</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 10  -18.51277 194.00000  8.6   69     5  10</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 11    7.00000 -21.37719  6.9   74     5  11</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 12   16.00000 256.00000  9.7   69     5  12</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 13   11.00000 290.00000  9.2   66     5  13</span>
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-<span class="r-out co"><span class="r-pr">#&gt;</span> 21    1.00000   8.00000  9.7   59     5  21</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 22   11.00000 320.00000 16.6   73     5  22</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 23    4.00000  25.00000  9.7   61     5  23</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 24   32.00000  92.00000 12.0   61     5  24</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 25  -17.81863  66.00000 16.6   57     5  25</span>
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-<span class="r-out co"><span class="r-pr">#&gt;</span> 134  44.00000 236.00000 14.9   81     9  11</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 135  21.00000 259.00000 15.5   76     9  12</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 136  28.00000 238.00000  6.3   77     9  13</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 137   9.00000  24.00000 10.9   71     9  14</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 138  13.00000 112.00000 11.5   71     9  15</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 139  46.00000 237.00000  6.9   78     9  16</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 140  18.00000 224.00000 13.8   67     9  17</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 141  13.00000  27.00000 10.3   76     9  18</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 142  24.00000 238.00000 10.3   68     9  19</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 143  16.00000 201.00000  8.0   82     9  20</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 144  13.00000 238.00000 12.6   64     9  21</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 145  23.00000  14.00000  9.2   71     9  22</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 146  36.00000 139.00000 10.3   81     9  23</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 147   7.00000  49.00000 10.3   69     9  24</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 148  14.00000  20.00000 16.6   63     9  25</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 149  30.00000 193.00000  6.9   70     9  26</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 150 -14.83089 145.00000 13.2   77     9  27</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 151  14.00000 191.00000 14.3   75     9  28</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 152  18.00000 131.00000  8.0   76     9  29</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 153  20.00000 223.00000 11.5   68     9  30</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/impute_knn.html b/docs/reference/impute_knn.html
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-    <h1>Impute nearest neighbours</h1>
-    <small class="dont-index">Source: <a href='https://github.com/njtierney/naniar/blob/master/R/impute_knn.R'><code>R/impute_knn.R</code></a></small>
-    <div class="hidden name"><code>impute_knn.Rd</code></div>
-    </div>
-
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-    
-    <p>Impute nearest neighbours</p>
-    
-    </div>
-
-    <pre class="usage"><span class='fu'>impute_knn</span>(<span class='no'>.tbl</span>, <span class='kw'>k</span> <span class='kw'>=</span> <span class='fl'>5</span>, <span class='kw'>method</span> <span class='kw'>=</span> <span class='st'>"mean"</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>.tbl</th>
-      <td><p>data.frame with missing values</p></td>
-    </tr>
-    <tr>
-      <th>k</th>
-      <td><p>integer, default value 5</p></td>
-    </tr>
-    <tr>
-      <th>method</th>
-      <td><ul>
-<li><p>"mean" or "random" - do you want to take the mean of the k
-neighbours, do you want to take a random value from the k neighbours.</p></li>
-</ul></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>data.frame with imputed values</p>
-    
-    <h2 class="hasAnchor" id="note"><a class="anchor" href="#note"></a>Note</h2>
-
-    <p>need to add separate functions for knn_avg and knn_rand, and also
-scoped variants. Ideally, this should work on a vector first, with
-different methods for each part</p>
-    
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='no'>airquality</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='bind_shadow.html'>bind_shadow</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>impute_knn</span>(<span class='st'>"mean"</span>)</div><div class='output co'>#&gt; # A tibble: 153 x 12
-#&gt;    Ozone Solar.R  Wind  Temp Month   Day Ozone_NA Solar.R_NA Wind_NA Temp_NA
-#&gt;    &lt;dbl&gt;   &lt;dbl&gt; &lt;dbl&gt; &lt;int&gt; &lt;int&gt; &lt;int&gt; &lt;fct&gt;    &lt;fct&gt;      &lt;fct&gt;   &lt;fct&gt;  
-#&gt;  1  41      190    7.4    67     5     1 !NA      !NA        !NA     !NA    
-#&gt;  2  36      118    8      72     5     2 !NA      !NA        !NA     !NA    
-#&gt;  3  12      149   12.6    74     5     3 !NA      !NA        !NA     !NA    
-#&gt;  4  18      313   11.5    62     5     4 !NA      !NA        !NA     !NA    
-#&gt;  5  42.1    185.  14.3    56     5     5 NA       NA         !NA     !NA    
-#&gt;  6  28      185.  14.9    66     5     6 !NA      NA         !NA     !NA    
-#&gt;  7  23      299    8.6    65     5     7 !NA      !NA        !NA     !NA    
-#&gt;  8  19       99   13.8    59     5     8 !NA      !NA        !NA     !NA    
-#&gt;  9   8       19   20.1    61     5     9 !NA      !NA        !NA     !NA    
-#&gt; 10  42.1    194    8.6    69     5    10 NA       !NA        !NA     !NA    
-#&gt; # ... with 143 more rows, and 2 more variables: Month_NA &lt;fct&gt;, Day_NA &lt;fct&gt;</div><div class='input'>
-</div><span class='co'># NOT RUN {</span>
-<span class='fu'>library</span>(<span class='no'>ggplot2</span>)
-<span class='no'>airquality</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='bind_shadow.html'>bind_shadow</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>impute_knn</span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='add_label_shadow.html'>add_label_shadow</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='http://www.rdocumentation.org/packages/ggplot2/topics/ggplot'>ggplot</a></span>(<span class='fu'><a href='http://www.rdocumentation.org/packages/ggplot2/topics/aes'>aes</a></span>(<span class='kw'>x</span> <span class='kw'>=</span> <span class='no'>Ozone</span>,
-             <span class='kw'>y</span> <span class='kw'>=</span> <span class='no'>Solar.R</span>,
-             <span class='kw'>colour</span> <span class='kw'>=</span> <span class='no'>any_missing</span>)) +
-         <span class='fu'><a href='http://www.rdocumentation.org/packages/ggplot2/topics/geom_point'>geom_point</a></span>()
-<span class='co'># }</span></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
-      <li><a href="#arguments">Arguments</a></li>
-      
-      <li><a href="#value">Value</a></li>
-
-      <li><a href="#note">Note</a></li>
-      
-      <li><a href="#examples">Examples</a></li>
-    </ul>
-
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-</div>
-
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-      <div class="copyright">
-  <p>Developed by Nicholas Tierney, Di Cook, Miles McBain, Colin Fay.</p>
-</div>
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diff --git a/docs/reference/impute_mean.html b/docs/reference/impute_mean.html
deleted file mode 100644
index b62f1786..00000000
--- a/docs/reference/impute_mean.html
+++ /dev/null
@@ -1,122 +0,0 @@
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-      <img src="../logo.png" class="logo" alt=""><h1>Impute the mean value into a vector with missing values</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/impute_mean.R" class="external-link"><code>R/impute_mean.R</code></a></small>
-      <div class="d-none name"><code>impute_mean.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Impute the mean value into a vector with missing values</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">impute_mean</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span>
-<span></span>
-<span><span class="co"># S3 method for default</span></span>
-<span><span class="fu">impute_mean</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span>
-<span></span>
-<span><span class="co"># S3 method for factor</span></span>
-<span><span class="fu">impute_mean</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
-<dd><p>vector</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>vector with mean values replaced</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">vec</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/stats/Normal.html" class="external-link">rnorm</a></span><span class="op">(</span><span class="fl">10</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">vec</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/sample.html" class="external-link">sample</a></span><span class="op">(</span><span class="fl">1</span><span class="op">:</span><span class="fl">10</span>, <span class="fl">3</span><span class="op">)</span><span class="op">]</span> <span class="op">&lt;-</span> <span class="cn">NA</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">impute_mean</span><span class="op">(</span><span class="va">vec</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [1] -0.008593142 -0.530161130 -0.561854135  0.509078646  0.115911160</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [6]  0.036688637 -0.252584949  0.036688637  0.985024011  0.036688637</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/impute_median.html b/docs/reference/impute_median.html
deleted file mode 100644
index bb47bad7..00000000
--- a/docs/reference/impute_median.html
+++ /dev/null
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-      <img src="../logo.png" class="logo" alt=""><h1>Impute the median value into a vector with missing values</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/impute-median.R" class="external-link"><code>R/impute-median.R</code></a></small>
-      <div class="d-none name"><code>impute_median.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Impute the median value into a vector with missing values</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">impute_median</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span>
-<span></span>
-<span><span class="co"># S3 method for default</span></span>
-<span><span class="fu">impute_median</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span>
-<span></span>
-<span><span class="co"># S3 method for factor</span></span>
-<span><span class="fu">impute_median</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
-<dd><p>vector</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>vector with median values replaced</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">vec</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/stats/Normal.html" class="external-link">rnorm</a></span><span class="op">(</span><span class="fl">10</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">vec</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/sample.html" class="external-link">sample</a></span><span class="op">(</span><span class="fl">1</span><span class="op">:</span><span class="fl">10</span>, <span class="fl">3</span><span class="op">)</span><span class="op">]</span> <span class="op">&lt;-</span> <span class="cn">NA</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">impute_median</span><span class="op">(</span><span class="va">vec</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [1] -0.3795665 -0.5889187  1.4241911 -0.7945301 -0.8508759 -0.3795665</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [7] -0.3795665  0.6699887  1.0867538 -0.3795665</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
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-    <footer><div class="pkgdown-footer-left">
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diff --git a/docs/reference/impute_shift.html b/docs/reference/impute_shift.html
deleted file mode 100644
index aa445dbd..00000000
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-the data. impute_shift imputes values 10
-values, and for character or factor values adds a new string or label." />
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-    <h1>Impute data with values shifted 10% below range.</h1>
-    <small class="dont-index">Source: <a href='https://github.com/njtierney/naniar/blob/master/R/impute_shift.R'><code>R/impute_shift.R</code></a></small>
-    <div class="hidden name"><code>impute_shift.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    
-    <p>It can be useful in exploratory graphics to impute data outside the range of
-the data. <code>impute_shift</code> imputes values 10<!-- % below the range for numeric -->
-values, and for character or factor values adds a new string or label.</p>
-    
-    </div>
-
-    <pre class="usage"><span class='fu'>impute_shift</span>(<span class='no'>.tbl</span>, <span class='no'>...</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>.tbl</th>
-      <td><p>a data.frame</p></td>
-    </tr>
-    <tr>
-      <th>...</th>
-      <td><p>additional arguments</p></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>an dataset with values imputed</p>
-    
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'>
-<span class='co'># you can impute data like so:</span>
-<span class='no'>airquality</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'>impute_shift</span>()</div><div class='output co'>#&gt;         Ozone   Solar.R Wind Temp Month Day
-#&gt; 1    41.00000 190.00000  7.4   67     5   1
-#&gt; 2    36.00000 118.00000  8.0   72     5   2
-#&gt; 3    12.00000 149.00000 12.6   74     5   3
-#&gt; 4    18.00000 313.00000 11.5   62     5   4
-#&gt; 5   -19.72321 -33.57778 14.3   56     5   5
-#&gt; 6    28.00000 -33.07810 14.9   66     5   6
-#&gt; 7    23.00000 299.00000  8.6   65     5   7
-#&gt; 8    19.00000  99.00000 13.8   59     5   8
-#&gt; 9     8.00000  19.00000 20.1   61     5   9
-#&gt; 10  -18.51277 194.00000  8.6   69     5  10
-#&gt; 11    7.00000 -21.37719  6.9   74     5  11
-#&gt; 12   16.00000 256.00000  9.7   69     5  12
-#&gt; 13   11.00000 290.00000  9.2   66     5  13
-#&gt; 14   14.00000 274.00000 10.9   68     5  14
-#&gt; 15   18.00000  65.00000 13.2   58     5  15
-#&gt; 16   14.00000 334.00000 11.5   64     5  16
-#&gt; 17   34.00000 307.00000 12.0   66     5  17
-#&gt; 18    6.00000  78.00000 18.4   57     5  18
-#&gt; 19   30.00000 322.00000 11.5   68     5  19
-#&gt; 20   11.00000  44.00000  9.7   62     5  20
-#&gt; 21    1.00000   8.00000  9.7   59     5  21
-#&gt; 22   11.00000 320.00000 16.6   73     5  22
-#&gt; 23    4.00000  25.00000  9.7   61     5  23
-#&gt; 24   32.00000  92.00000 12.0   61     5  24
-#&gt; 25  -17.81863  66.00000 16.6   57     5  25
-#&gt; 26  -19.43853 266.00000 14.9   58     5  26
-#&gt; 27  -15.14310 -24.60954  8.0   57     5  27
-#&gt; 28   23.00000  13.00000 12.0   67     5  28
-#&gt; 29   45.00000 252.00000 14.9   81     5  29
-#&gt; 30  115.00000 223.00000  5.7   79     5  30
-#&gt; 31   37.00000 279.00000  7.4   76     5  31
-#&gt; 32  -16.17315 286.00000  8.6   78     6   1
-#&gt; 33  -14.65883 287.00000  9.7   74     6   2
-#&gt; 34  -17.85609 242.00000 16.1   67     6   3
-#&gt; 35  -13.29299 186.00000  9.2   84     6   4
-#&gt; 36  -16.16323 220.00000  8.6   85     6   5
-#&gt; 37  -19.60935 264.00000 14.3   79     6   6
-#&gt; 38   29.00000 127.00000  9.7   82     6   7
-#&gt; 39  -19.65780 273.00000  6.9   87     6   8
-#&gt; 40   71.00000 291.00000 13.8   90     6   9
-#&gt; 41   39.00000 323.00000 11.5   87     6  10
-#&gt; 42  -13.40961 259.00000 10.9   93     6  11
-#&gt; 43  -13.53728 250.00000  9.2   92     6  12
-#&gt; 44   23.00000 148.00000  8.0   82     6  13
-#&gt; 45  -19.65993 332.00000 13.8   80     6  14
-#&gt; 46  -16.48342 322.00000 11.5   79     6  15
-#&gt; 47   21.00000 191.00000 14.9   77     6  16
-#&gt; 48   37.00000 284.00000 20.7   72     6  17
-#&gt; 49   20.00000  37.00000  9.2   65     6  18
-#&gt; 50   12.00000 120.00000 11.5   73     6  19
-#&gt; 51   13.00000 137.00000 10.3   76     6  20
-#&gt; 52  -17.17718 150.00000  6.3   77     6  21
-#&gt; 53  -16.74073  59.00000  1.7   76     6  22
-#&gt; 54  -13.65786  91.00000  4.6   76     6  23
-#&gt; 55  -16.78786 250.00000  6.3   76     6  24
-#&gt; 56  -12.30098 135.00000  8.0   75     6  25
-#&gt; 57  -13.33171 127.00000  8.0   78     6  26
-#&gt; 58  -16.77414  47.00000 10.3   73     6  27
-#&gt; 59  -17.08225  98.00000 11.5   80     6  28
-#&gt; 60  -15.98818  31.00000 14.9   77     6  29
-#&gt; 61  -19.17558 138.00000  8.0   83     6  30
-#&gt; 62  135.00000 269.00000  4.1   84     7   1
-#&gt; 63   49.00000 248.00000  9.2   85     7   2
-#&gt; 64   32.00000 236.00000  9.2   81     7   3
-#&gt; 65  -14.27138 101.00000 10.9   84     7   4
-#&gt; 66   64.00000 175.00000  4.6   83     7   5
-#&gt; 67   40.00000 314.00000 10.9   83     7   6
-#&gt; 68   77.00000 276.00000  5.1   88     7   7
-#&gt; 69   97.00000 267.00000  6.3   92     7   8
-#&gt; 70   97.00000 272.00000  5.7   92     7   9
-#&gt; 71   85.00000 175.00000  7.4   89     7  10
-#&gt; 72  -13.51764 139.00000  8.6   82     7  11
-#&gt; 73   10.00000 264.00000 14.3   73     7  12
-#&gt; 74   27.00000 175.00000 14.9   81     7  13
-#&gt; 75  -13.48998 291.00000 14.9   91     7  14
-#&gt; 76    7.00000  48.00000 14.3   80     7  15
-#&gt; 77   48.00000 260.00000  6.9   81     7  16
-#&gt; 78   35.00000 274.00000 10.3   82     7  17
-#&gt; 79   61.00000 285.00000  6.3   84     7  18
-#&gt; 80   79.00000 187.00000  5.1   87     7  19
-#&gt; 81   63.00000 220.00000 11.5   85     7  20
-#&gt; 82   16.00000   7.00000  6.9   74     7  21
-#&gt; 83  -16.92150 258.00000  9.7   81     7  22
-#&gt; 84  -16.60335 295.00000 11.5   82     7  23
-#&gt; 85   80.00000 294.00000  8.6   86     7  24
-#&gt; 86  108.00000 223.00000  8.0   85     7  25
-#&gt; 87   20.00000  81.00000  8.6   82     7  26
-#&gt; 88   52.00000  82.00000 12.0   86     7  27
-#&gt; 89   82.00000 213.00000  7.4   88     7  28
-#&gt; 90   50.00000 275.00000  7.4   86     7  29
-#&gt; 91   64.00000 253.00000  7.4   83     7  30
-#&gt; 92   59.00000 254.00000  9.2   81     7  31
-#&gt; 93   39.00000  83.00000  6.9   81     8   1
-#&gt; 94    9.00000  24.00000 13.8   81     8   2
-#&gt; 95   16.00000  77.00000  7.4   82     8   3
-#&gt; 96   78.00000 -30.94374  6.9   86     8   4
-#&gt; 97   35.00000 -33.38707  7.4   85     8   5
-#&gt; 98   66.00000 -21.48980  4.6   87     8   6
-#&gt; 99  122.00000 255.00000  4.0   89     8   7
-#&gt; 100  89.00000 229.00000 10.3   90     8   8
-#&gt; 101 110.00000 207.00000  8.0   90     8   9
-#&gt; 102 -14.78907 222.00000  8.6   92     8  10
-#&gt; 103 -16.19151 137.00000 11.5   86     8  11
-#&gt; 104  44.00000 192.00000 11.5   86     8  12
-#&gt; 105  28.00000 273.00000 11.5   82     8  13
-#&gt; 106  65.00000 157.00000  9.7   80     8  14
-#&gt; 107 -19.73591  64.00000 11.5   79     8  15
-#&gt; 108  22.00000  71.00000 10.3   77     8  16
-#&gt; 109  59.00000  51.00000  6.3   79     8  17
-#&gt; 110  23.00000 115.00000  7.4   76     8  18
-#&gt; 111  31.00000 244.00000 10.9   78     8  19
-#&gt; 112  44.00000 190.00000 10.3   78     8  20
-#&gt; 113  21.00000 259.00000 15.5   77     8  21
-#&gt; 114   9.00000  36.00000 14.3   72     8  22
-#&gt; 115 -18.92235 255.00000 12.6   75     8  23
-#&gt; 116  45.00000 212.00000  9.7   79     8  24
-#&gt; 117 168.00000 238.00000  3.4   81     8  25
-#&gt; 118  73.00000 215.00000  8.0   86     8  26
-#&gt; 119 -14.86296 153.00000  5.7   88     8  27
-#&gt; 120  76.00000 203.00000  9.7   97     8  28
-#&gt; 121 118.00000 225.00000  2.3   94     8  29
-#&gt; 122  84.00000 237.00000  6.3   96     8  30
-#&gt; 123  85.00000 188.00000  6.3   94     8  31
-#&gt; 124  96.00000 167.00000  6.9   91     9   1
-#&gt; 125  78.00000 197.00000  5.1   92     9   2
-#&gt; 126  73.00000 183.00000  2.8   93     9   3
-#&gt; 127  91.00000 189.00000  4.6   93     9   4
-#&gt; 128  47.00000  95.00000  7.4   87     9   5
-#&gt; 129  32.00000  92.00000 15.5   84     9   6
-#&gt; 130  20.00000 252.00000 10.9   80     9   7
-#&gt; 131  23.00000 220.00000 10.3   78     9   8
-#&gt; 132  21.00000 230.00000 10.9   75     9   9
-#&gt; 133  24.00000 259.00000  9.7   73     9  10
-#&gt; 134  44.00000 236.00000 14.9   81     9  11
-#&gt; 135  21.00000 259.00000 15.5   76     9  12
-#&gt; 136  28.00000 238.00000  6.3   77     9  13
-#&gt; 137   9.00000  24.00000 10.9   71     9  14
-#&gt; 138  13.00000 112.00000 11.5   71     9  15
-#&gt; 139  46.00000 237.00000  6.9   78     9  16
-#&gt; 140  18.00000 224.00000 13.8   67     9  17
-#&gt; 141  13.00000  27.00000 10.3   76     9  18
-#&gt; 142  24.00000 238.00000 10.3   68     9  19
-#&gt; 143  16.00000 201.00000  8.0   82     9  20
-#&gt; 144  13.00000 238.00000 12.6   64     9  21
-#&gt; 145  23.00000  14.00000  9.2   71     9  22
-#&gt; 146  36.00000 139.00000 10.3   81     9  23
-#&gt; 147   7.00000  49.00000 10.3   69     9  24
-#&gt; 148  14.00000  20.00000 16.6   63     9  25
-#&gt; 149  30.00000 193.00000  6.9   70     9  26
-#&gt; 150 -14.83089 145.00000 13.2   77     9  27
-#&gt; 151  14.00000 191.00000 14.3   75     9  28
-#&gt; 152  18.00000 131.00000  8.0   76     9  29
-#&gt; 153  20.00000 223.00000 11.5   68     9  30</div><div class='input'>
-<span class='co'># However, this does not show you WHERE the missing values are.</span>
-<span class='co'># to keep track of them, you want to use `bind_shadow()` first.</span>
-
-<span class='no'>airquality</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='bind_shadow.html'>bind_shadow</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>impute_shift</span>()</div><div class='output co'>#&gt; # A tibble: 153 x 12
-#&gt;     Ozone Solar.R  Wind  Temp Month   Day Ozone_NA Solar.R_NA Wind_NA Temp_NA
-#&gt;     &lt;dbl&gt;   &lt;dbl&gt; &lt;dbl&gt; &lt;int&gt; &lt;int&gt; &lt;int&gt; &lt;fct&gt;    &lt;fct&gt;      &lt;fct&gt;   &lt;fct&gt;  
-#&gt;  1  41.0    190.   7.40    67     5     1 !NA      !NA        !NA     !NA    
-#&gt;  2  36.0    118.   8.00    72     5     2 !NA      !NA        !NA     !NA    
-#&gt;  3  12.0    149.  12.6     74     5     3 !NA      !NA        !NA     !NA    
-#&gt;  4  18.0    313.  11.5     62     5     4 !NA      !NA        !NA     !NA    
-#&gt;  5 -19.7    -33.6 14.3     56     5     5 NA       NA         !NA     !NA    
-#&gt;  6  28.0    -33.1 14.9     66     5     6 !NA      NA         !NA     !NA    
-#&gt;  7  23.0    299.   8.60    65     5     7 !NA      !NA        !NA     !NA    
-#&gt;  8  19.0     99.0 13.8     59     5     8 !NA      !NA        !NA     !NA    
-#&gt;  9   8.00    19.0 20.1     61     5     9 !NA      !NA        !NA     !NA    
-#&gt; 10 -18.5    194.   8.60    69     5    10 NA       !NA        !NA     !NA    
-#&gt; # ... with 143 more rows, and 2 more variables: Month_NA &lt;fct&gt;, Day_NA &lt;fct&gt;</div><div class='input'>
-<span class='co'># This identifies where the missing values are located, which means you</span>
-<span class='co'># can do things like this:</span>
-
-<span class='fu'>library</span>(<span class='no'>ggplot2</span>)
-<span class='no'>airquality</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='bind_shadow.html'>bind_shadow</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>impute_shift</span>() <span class='kw'>%&gt;%</span>
-  <span class='co'># identify where there are missings across rows.</span>
-  <span class='fu'><a href='add_label_shadow.html'>add_label_shadow</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='http://www.rdocumentation.org/packages/ggplot2/topics/ggplot'>ggplot</a></span>(<span class='fu'><a href='http://www.rdocumentation.org/packages/ggplot2/topics/aes'>aes</a></span>(<span class='kw'>x</span> <span class='kw'>=</span> <span class='no'>Ozone</span>,
-             <span class='kw'>y</span> <span class='kw'>=</span> <span class='no'>Solar.R</span>,
-             <span class='kw'>colour</span> <span class='kw'>=</span> <span class='no'>any_missing</span>)) +
-  <span class='fu'><a href='http://www.rdocumentation.org/packages/ggplot2/topics/geom_point'>geom_point</a></span>()</div><div class='img'><img src='impute_shift-1.png' alt='' width='700' height='433' /></div><div class='input'>
-# This is a long version of `geom_miss_point()`.
-
-</div></pre>
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-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
-      <li><a href="#arguments">Arguments</a></li>
-      
-      <li><a href="#value">Value</a></li>
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-    </ul>
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-that satisfy a specific condition, use the scoped variants,
-impute_shift_at, and impute_shift_if." />
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-<div class="row">
-  <div class="col-md-9 contents">
-    <div class="page-header">
-    <h1>Scoped variants of <code>impute_shift</code></h1>
-    <small class="dont-index">Source: <a href='https://github.com/njtierney/naniar/blob/master/R/impute_shift.R'><code>R/impute_shift.R</code></a></small>
-    <div class="hidden name"><code>impute_shift_at.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    
-    <p><code>impute_shift</code> operates on all variables. To only impute variables
-that satisfy a specific condition, use the scoped variants,
-<code>impute_shift_at</code>, and <code>impute_shift_if</code>.</p>
-    
-    </div>
-
-    <pre class="usage"><span class='fu'>impute_shift_at</span>(<span class='no'>.tbl</span>, <span class='no'>.vars</span>, <span class='no'>...</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>.tbl</th>
-      <td><p>a data.frame</p></td>
-    </tr>
-    <tr>
-      <th>.vars</th>
-      <td><p>variables to impute</p></td>
-    </tr>
-    <tr>
-      <th>...</th>
-      <td><p>extra arguments</p></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>an dataset with values imputed</p>
-    
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># select variables starting with a particular string.</span>
-<span class='fu'>library</span>(<span class='no'>dplyr</span>)</div><div class='output co'>#&gt; <span class='message'></span>
-#&gt; <span class='message'>Attaching package: ‘dplyr’</span></div><div class='output co'>#&gt; <span class='message'>The following objects are masked from ‘package:stats’:</span>
-#&gt; <span class='message'></span>
-#&gt; <span class='message'>    filter, lag</span></div><div class='output co'>#&gt; <span class='message'>The following object is masked from ‘package:testthat’:</span>
-#&gt; <span class='message'></span>
-#&gt; <span class='message'>    matches</span></div><div class='output co'>#&gt; <span class='message'>The following objects are masked from ‘package:base’:</span>
-#&gt; <span class='message'></span>
-#&gt; <span class='message'>    intersect, setdiff, setequal, union</span></div><div class='input'><span class='fu'>impute_shift_at</span>(<span class='no'>airquality</span>,
-                <span class='kw'>.vars</span> <span class='kw'>=</span> <span class='fu'><a href='http://dplyr.tidyverse.org/reference/select_helpers.html'>starts_with</a></span>(<span class='st'>"Oz"</span>))</div><div class='output co'>#&gt;         Ozone Solar.R Wind Temp Month Day
-#&gt; 1    41.00000     190  7.4   67     5   1
-#&gt; 2    36.00000     118  8.0   72     5   2
-#&gt; 3    12.00000     149 12.6   74     5   3
-#&gt; 4    18.00000     313 11.5   62     5   4
-#&gt; 5   -19.72321      NA 14.3   56     5   5
-#&gt; 6    28.00000      NA 14.9   66     5   6
-#&gt; 7    23.00000     299  8.6   65     5   7
-#&gt; 8    19.00000      99 13.8   59     5   8
-#&gt; 9     8.00000      19 20.1   61     5   9
-#&gt; 10  -18.51277     194  8.6   69     5  10
-#&gt; 11    7.00000      NA  6.9   74     5  11
-#&gt; 12   16.00000     256  9.7   69     5  12
-#&gt; 13   11.00000     290  9.2   66     5  13
-#&gt; 14   14.00000     274 10.9   68     5  14
-#&gt; 15   18.00000      65 13.2   58     5  15
-#&gt; 16   14.00000     334 11.5   64     5  16
-#&gt; 17   34.00000     307 12.0   66     5  17
-#&gt; 18    6.00000      78 18.4   57     5  18
-#&gt; 19   30.00000     322 11.5   68     5  19
-#&gt; 20   11.00000      44  9.7   62     5  20
-#&gt; 21    1.00000       8  9.7   59     5  21
-#&gt; 22   11.00000     320 16.6   73     5  22
-#&gt; 23    4.00000      25  9.7   61     5  23
-#&gt; 24   32.00000      92 12.0   61     5  24
-#&gt; 25  -17.81863      66 16.6   57     5  25
-#&gt; 26  -19.43853     266 14.9   58     5  26
-#&gt; 27  -15.14310      NA  8.0   57     5  27
-#&gt; 28   23.00000      13 12.0   67     5  28
-#&gt; 29   45.00000     252 14.9   81     5  29
-#&gt; 30  115.00000     223  5.7   79     5  30
-#&gt; 31   37.00000     279  7.4   76     5  31
-#&gt; 32  -16.17315     286  8.6   78     6   1
-#&gt; 33  -14.65883     287  9.7   74     6   2
-#&gt; 34  -17.85609     242 16.1   67     6   3
-#&gt; 35  -13.29299     186  9.2   84     6   4
-#&gt; 36  -16.16323     220  8.6   85     6   5
-#&gt; 37  -19.60935     264 14.3   79     6   6
-#&gt; 38   29.00000     127  9.7   82     6   7
-#&gt; 39  -19.65780     273  6.9   87     6   8
-#&gt; 40   71.00000     291 13.8   90     6   9
-#&gt; 41   39.00000     323 11.5   87     6  10
-#&gt; 42  -13.40961     259 10.9   93     6  11
-#&gt; 43  -13.53728     250  9.2   92     6  12
-#&gt; 44   23.00000     148  8.0   82     6  13
-#&gt; 45  -19.65993     332 13.8   80     6  14
-#&gt; 46  -16.48342     322 11.5   79     6  15
-#&gt; 47   21.00000     191 14.9   77     6  16
-#&gt; 48   37.00000     284 20.7   72     6  17
-#&gt; 49   20.00000      37  9.2   65     6  18
-#&gt; 50   12.00000     120 11.5   73     6  19
-#&gt; 51   13.00000     137 10.3   76     6  20
-#&gt; 52  -17.17718     150  6.3   77     6  21
-#&gt; 53  -16.74073      59  1.7   76     6  22
-#&gt; 54  -13.65786      91  4.6   76     6  23
-#&gt; 55  -16.78786     250  6.3   76     6  24
-#&gt; 56  -12.30098     135  8.0   75     6  25
-#&gt; 57  -13.33171     127  8.0   78     6  26
-#&gt; 58  -16.77414      47 10.3   73     6  27
-#&gt; 59  -17.08225      98 11.5   80     6  28
-#&gt; 60  -15.98818      31 14.9   77     6  29
-#&gt; 61  -19.17558     138  8.0   83     6  30
-#&gt; 62  135.00000     269  4.1   84     7   1
-#&gt; 63   49.00000     248  9.2   85     7   2
-#&gt; 64   32.00000     236  9.2   81     7   3
-#&gt; 65  -14.27138     101 10.9   84     7   4
-#&gt; 66   64.00000     175  4.6   83     7   5
-#&gt; 67   40.00000     314 10.9   83     7   6
-#&gt; 68   77.00000     276  5.1   88     7   7
-#&gt; 69   97.00000     267  6.3   92     7   8
-#&gt; 70   97.00000     272  5.7   92     7   9
-#&gt; 71   85.00000     175  7.4   89     7  10
-#&gt; 72  -13.51764     139  8.6   82     7  11
-#&gt; 73   10.00000     264 14.3   73     7  12
-#&gt; 74   27.00000     175 14.9   81     7  13
-#&gt; 75  -13.48998     291 14.9   91     7  14
-#&gt; 76    7.00000      48 14.3   80     7  15
-#&gt; 77   48.00000     260  6.9   81     7  16
-#&gt; 78   35.00000     274 10.3   82     7  17
-#&gt; 79   61.00000     285  6.3   84     7  18
-#&gt; 80   79.00000     187  5.1   87     7  19
-#&gt; 81   63.00000     220 11.5   85     7  20
-#&gt; 82   16.00000       7  6.9   74     7  21
-#&gt; 83  -16.92150     258  9.7   81     7  22
-#&gt; 84  -16.60335     295 11.5   82     7  23
-#&gt; 85   80.00000     294  8.6   86     7  24
-#&gt; 86  108.00000     223  8.0   85     7  25
-#&gt; 87   20.00000      81  8.6   82     7  26
-#&gt; 88   52.00000      82 12.0   86     7  27
-#&gt; 89   82.00000     213  7.4   88     7  28
-#&gt; 90   50.00000     275  7.4   86     7  29
-#&gt; 91   64.00000     253  7.4   83     7  30
-#&gt; 92   59.00000     254  9.2   81     7  31
-#&gt; 93   39.00000      83  6.9   81     8   1
-#&gt; 94    9.00000      24 13.8   81     8   2
-#&gt; 95   16.00000      77  7.4   82     8   3
-#&gt; 96   78.00000      NA  6.9   86     8   4
-#&gt; 97   35.00000      NA  7.4   85     8   5
-#&gt; 98   66.00000      NA  4.6   87     8   6
-#&gt; 99  122.00000     255  4.0   89     8   7
-#&gt; 100  89.00000     229 10.3   90     8   8
-#&gt; 101 110.00000     207  8.0   90     8   9
-#&gt; 102 -14.78907     222  8.6   92     8  10
-#&gt; 103 -16.19151     137 11.5   86     8  11
-#&gt; 104  44.00000     192 11.5   86     8  12
-#&gt; 105  28.00000     273 11.5   82     8  13
-#&gt; 106  65.00000     157  9.7   80     8  14
-#&gt; 107 -19.73591      64 11.5   79     8  15
-#&gt; 108  22.00000      71 10.3   77     8  16
-#&gt; 109  59.00000      51  6.3   79     8  17
-#&gt; 110  23.00000     115  7.4   76     8  18
-#&gt; 111  31.00000     244 10.9   78     8  19
-#&gt; 112  44.00000     190 10.3   78     8  20
-#&gt; 113  21.00000     259 15.5   77     8  21
-#&gt; 114   9.00000      36 14.3   72     8  22
-#&gt; 115 -18.92235     255 12.6   75     8  23
-#&gt; 116  45.00000     212  9.7   79     8  24
-#&gt; 117 168.00000     238  3.4   81     8  25
-#&gt; 118  73.00000     215  8.0   86     8  26
-#&gt; 119 -14.86296     153  5.7   88     8  27
-#&gt; 120  76.00000     203  9.7   97     8  28
-#&gt; 121 118.00000     225  2.3   94     8  29
-#&gt; 122  84.00000     237  6.3   96     8  30
-#&gt; 123  85.00000     188  6.3   94     8  31
-#&gt; 124  96.00000     167  6.9   91     9   1
-#&gt; 125  78.00000     197  5.1   92     9   2
-#&gt; 126  73.00000     183  2.8   93     9   3
-#&gt; 127  91.00000     189  4.6   93     9   4
-#&gt; 128  47.00000      95  7.4   87     9   5
-#&gt; 129  32.00000      92 15.5   84     9   6
-#&gt; 130  20.00000     252 10.9   80     9   7
-#&gt; 131  23.00000     220 10.3   78     9   8
-#&gt; 132  21.00000     230 10.9   75     9   9
-#&gt; 133  24.00000     259  9.7   73     9  10
-#&gt; 134  44.00000     236 14.9   81     9  11
-#&gt; 135  21.00000     259 15.5   76     9  12
-#&gt; 136  28.00000     238  6.3   77     9  13
-#&gt; 137   9.00000      24 10.9   71     9  14
-#&gt; 138  13.00000     112 11.5   71     9  15
-#&gt; 139  46.00000     237  6.9   78     9  16
-#&gt; 140  18.00000     224 13.8   67     9  17
-#&gt; 141  13.00000      27 10.3   76     9  18
-#&gt; 142  24.00000     238 10.3   68     9  19
-#&gt; 143  16.00000     201  8.0   82     9  20
-#&gt; 144  13.00000     238 12.6   64     9  21
-#&gt; 145  23.00000      14  9.2   71     9  22
-#&gt; 146  36.00000     139 10.3   81     9  23
-#&gt; 147   7.00000      49 10.3   69     9  24
-#&gt; 148  14.00000      20 16.6   63     9  25
-#&gt; 149  30.00000     193  6.9   70     9  26
-#&gt; 150 -14.83089     145 13.2   77     9  27
-#&gt; 151  14.00000     191 14.3   75     9  28
-#&gt; 152  18.00000     131  8.0   76     9  29
-#&gt; 153  20.00000     223 11.5   68     9  30</div><div class='input'>
-<span class='fu'>impute_shift_at</span>(<span class='no'>airquality</span>,
-                <span class='kw'>.vars</span> <span class='kw'>=</span> <span class='fl'>1</span>:<span class='fl'>2</span>)</div><div class='output co'>#&gt;         Ozone   Solar.R Wind Temp Month Day
-#&gt; 1    41.00000 190.00000  7.4   67     5   1
-#&gt; 2    36.00000 118.00000  8.0   72     5   2
-#&gt; 3    12.00000 149.00000 12.6   74     5   3
-#&gt; 4    18.00000 313.00000 11.5   62     5   4
-#&gt; 5   -19.72321 -33.57778 14.3   56     5   5
-#&gt; 6    28.00000 -33.07810 14.9   66     5   6
-#&gt; 7    23.00000 299.00000  8.6   65     5   7
-#&gt; 8    19.00000  99.00000 13.8   59     5   8
-#&gt; 9     8.00000  19.00000 20.1   61     5   9
-#&gt; 10  -18.51277 194.00000  8.6   69     5  10
-#&gt; 11    7.00000 -21.37719  6.9   74     5  11
-#&gt; 12   16.00000 256.00000  9.7   69     5  12
-#&gt; 13   11.00000 290.00000  9.2   66     5  13
-#&gt; 14   14.00000 274.00000 10.9   68     5  14
-#&gt; 15   18.00000  65.00000 13.2   58     5  15
-#&gt; 16   14.00000 334.00000 11.5   64     5  16
-#&gt; 17   34.00000 307.00000 12.0   66     5  17
-#&gt; 18    6.00000  78.00000 18.4   57     5  18
-#&gt; 19   30.00000 322.00000 11.5   68     5  19
-#&gt; 20   11.00000  44.00000  9.7   62     5  20
-#&gt; 21    1.00000   8.00000  9.7   59     5  21
-#&gt; 22   11.00000 320.00000 16.6   73     5  22
-#&gt; 23    4.00000  25.00000  9.7   61     5  23
-#&gt; 24   32.00000  92.00000 12.0   61     5  24
-#&gt; 25  -17.81863  66.00000 16.6   57     5  25
-#&gt; 26  -19.43853 266.00000 14.9   58     5  26
-#&gt; 27  -15.14310 -24.60954  8.0   57     5  27
-#&gt; 28   23.00000  13.00000 12.0   67     5  28
-#&gt; 29   45.00000 252.00000 14.9   81     5  29
-#&gt; 30  115.00000 223.00000  5.7   79     5  30
-#&gt; 31   37.00000 279.00000  7.4   76     5  31
-#&gt; 32  -16.17315 286.00000  8.6   78     6   1
-#&gt; 33  -14.65883 287.00000  9.7   74     6   2
-#&gt; 34  -17.85609 242.00000 16.1   67     6   3
-#&gt; 35  -13.29299 186.00000  9.2   84     6   4
-#&gt; 36  -16.16323 220.00000  8.6   85     6   5
-#&gt; 37  -19.60935 264.00000 14.3   79     6   6
-#&gt; 38   29.00000 127.00000  9.7   82     6   7
-#&gt; 39  -19.65780 273.00000  6.9   87     6   8
-#&gt; 40   71.00000 291.00000 13.8   90     6   9
-#&gt; 41   39.00000 323.00000 11.5   87     6  10
-#&gt; 42  -13.40961 259.00000 10.9   93     6  11
-#&gt; 43  -13.53728 250.00000  9.2   92     6  12
-#&gt; 44   23.00000 148.00000  8.0   82     6  13
-#&gt; 45  -19.65993 332.00000 13.8   80     6  14
-#&gt; 46  -16.48342 322.00000 11.5   79     6  15
-#&gt; 47   21.00000 191.00000 14.9   77     6  16
-#&gt; 48   37.00000 284.00000 20.7   72     6  17
-#&gt; 49   20.00000  37.00000  9.2   65     6  18
-#&gt; 50   12.00000 120.00000 11.5   73     6  19
-#&gt; 51   13.00000 137.00000 10.3   76     6  20
-#&gt; 52  -17.17718 150.00000  6.3   77     6  21
-#&gt; 53  -16.74073  59.00000  1.7   76     6  22
-#&gt; 54  -13.65786  91.00000  4.6   76     6  23
-#&gt; 55  -16.78786 250.00000  6.3   76     6  24
-#&gt; 56  -12.30098 135.00000  8.0   75     6  25
-#&gt; 57  -13.33171 127.00000  8.0   78     6  26
-#&gt; 58  -16.77414  47.00000 10.3   73     6  27
-#&gt; 59  -17.08225  98.00000 11.5   80     6  28
-#&gt; 60  -15.98818  31.00000 14.9   77     6  29
-#&gt; 61  -19.17558 138.00000  8.0   83     6  30
-#&gt; 62  135.00000 269.00000  4.1   84     7   1
-#&gt; 63   49.00000 248.00000  9.2   85     7   2
-#&gt; 64   32.00000 236.00000  9.2   81     7   3
-#&gt; 65  -14.27138 101.00000 10.9   84     7   4
-#&gt; 66   64.00000 175.00000  4.6   83     7   5
-#&gt; 67   40.00000 314.00000 10.9   83     7   6
-#&gt; 68   77.00000 276.00000  5.1   88     7   7
-#&gt; 69   97.00000 267.00000  6.3   92     7   8
-#&gt; 70   97.00000 272.00000  5.7   92     7   9
-#&gt; 71   85.00000 175.00000  7.4   89     7  10
-#&gt; 72  -13.51764 139.00000  8.6   82     7  11
-#&gt; 73   10.00000 264.00000 14.3   73     7  12
-#&gt; 74   27.00000 175.00000 14.9   81     7  13
-#&gt; 75  -13.48998 291.00000 14.9   91     7  14
-#&gt; 76    7.00000  48.00000 14.3   80     7  15
-#&gt; 77   48.00000 260.00000  6.9   81     7  16
-#&gt; 78   35.00000 274.00000 10.3   82     7  17
-#&gt; 79   61.00000 285.00000  6.3   84     7  18
-#&gt; 80   79.00000 187.00000  5.1   87     7  19
-#&gt; 81   63.00000 220.00000 11.5   85     7  20
-#&gt; 82   16.00000   7.00000  6.9   74     7  21
-#&gt; 83  -16.92150 258.00000  9.7   81     7  22
-#&gt; 84  -16.60335 295.00000 11.5   82     7  23
-#&gt; 85   80.00000 294.00000  8.6   86     7  24
-#&gt; 86  108.00000 223.00000  8.0   85     7  25
-#&gt; 87   20.00000  81.00000  8.6   82     7  26
-#&gt; 88   52.00000  82.00000 12.0   86     7  27
-#&gt; 89   82.00000 213.00000  7.4   88     7  28
-#&gt; 90   50.00000 275.00000  7.4   86     7  29
-#&gt; 91   64.00000 253.00000  7.4   83     7  30
-#&gt; 92   59.00000 254.00000  9.2   81     7  31
-#&gt; 93   39.00000  83.00000  6.9   81     8   1
-#&gt; 94    9.00000  24.00000 13.8   81     8   2
-#&gt; 95   16.00000  77.00000  7.4   82     8   3
-#&gt; 96   78.00000 -30.94374  6.9   86     8   4
-#&gt; 97   35.00000 -33.38707  7.4   85     8   5
-#&gt; 98   66.00000 -21.48980  4.6   87     8   6
-#&gt; 99  122.00000 255.00000  4.0   89     8   7
-#&gt; 100  89.00000 229.00000 10.3   90     8   8
-#&gt; 101 110.00000 207.00000  8.0   90     8   9
-#&gt; 102 -14.78907 222.00000  8.6   92     8  10
-#&gt; 103 -16.19151 137.00000 11.5   86     8  11
-#&gt; 104  44.00000 192.00000 11.5   86     8  12
-#&gt; 105  28.00000 273.00000 11.5   82     8  13
-#&gt; 106  65.00000 157.00000  9.7   80     8  14
-#&gt; 107 -19.73591  64.00000 11.5   79     8  15
-#&gt; 108  22.00000  71.00000 10.3   77     8  16
-#&gt; 109  59.00000  51.00000  6.3   79     8  17
-#&gt; 110  23.00000 115.00000  7.4   76     8  18
-#&gt; 111  31.00000 244.00000 10.9   78     8  19
-#&gt; 112  44.00000 190.00000 10.3   78     8  20
-#&gt; 113  21.00000 259.00000 15.5   77     8  21
-#&gt; 114   9.00000  36.00000 14.3   72     8  22
-#&gt; 115 -18.92235 255.00000 12.6   75     8  23
-#&gt; 116  45.00000 212.00000  9.7   79     8  24
-#&gt; 117 168.00000 238.00000  3.4   81     8  25
-#&gt; 118  73.00000 215.00000  8.0   86     8  26
-#&gt; 119 -14.86296 153.00000  5.7   88     8  27
-#&gt; 120  76.00000 203.00000  9.7   97     8  28
-#&gt; 121 118.00000 225.00000  2.3   94     8  29
-#&gt; 122  84.00000 237.00000  6.3   96     8  30
-#&gt; 123  85.00000 188.00000  6.3   94     8  31
-#&gt; 124  96.00000 167.00000  6.9   91     9   1
-#&gt; 125  78.00000 197.00000  5.1   92     9   2
-#&gt; 126  73.00000 183.00000  2.8   93     9   3
-#&gt; 127  91.00000 189.00000  4.6   93     9   4
-#&gt; 128  47.00000  95.00000  7.4   87     9   5
-#&gt; 129  32.00000  92.00000 15.5   84     9   6
-#&gt; 130  20.00000 252.00000 10.9   80     9   7
-#&gt; 131  23.00000 220.00000 10.3   78     9   8
-#&gt; 132  21.00000 230.00000 10.9   75     9   9
-#&gt; 133  24.00000 259.00000  9.7   73     9  10
-#&gt; 134  44.00000 236.00000 14.9   81     9  11
-#&gt; 135  21.00000 259.00000 15.5   76     9  12
-#&gt; 136  28.00000 238.00000  6.3   77     9  13
-#&gt; 137   9.00000  24.00000 10.9   71     9  14
-#&gt; 138  13.00000 112.00000 11.5   71     9  15
-#&gt; 139  46.00000 237.00000  6.9   78     9  16
-#&gt; 140  18.00000 224.00000 13.8   67     9  17
-#&gt; 141  13.00000  27.00000 10.3   76     9  18
-#&gt; 142  24.00000 238.00000 10.3   68     9  19
-#&gt; 143  16.00000 201.00000  8.0   82     9  20
-#&gt; 144  13.00000 238.00000 12.6   64     9  21
-#&gt; 145  23.00000  14.00000  9.2   71     9  22
-#&gt; 146  36.00000 139.00000 10.3   81     9  23
-#&gt; 147   7.00000  49.00000 10.3   69     9  24
-#&gt; 148  14.00000  20.00000 16.6   63     9  25
-#&gt; 149  30.00000 193.00000  6.9   70     9  26
-#&gt; 150 -14.83089 145.00000 13.2   77     9  27
-#&gt; 151  14.00000 191.00000 14.3   75     9  28
-#&gt; 152  18.00000 131.00000  8.0   76     9  29
-#&gt; 153  20.00000 223.00000 11.5   68     9  30</div><div class='input'>
-<span class='fu'>impute_shift_at</span>(<span class='no'>airquality</span>,
-                <span class='kw'>.vars</span> <span class='kw'>=</span> <span class='fu'><a href='http://dplyr.tidyverse.org/reference/select_helpers.html'>everything</a></span>())</div><div class='output co'>#&gt;         Ozone   Solar.R Wind Temp Month Day
-#&gt; 1    41.00000 190.00000  7.4   67     5   1
-#&gt; 2    36.00000 118.00000  8.0   72     5   2
-#&gt; 3    12.00000 149.00000 12.6   74     5   3
-#&gt; 4    18.00000 313.00000 11.5   62     5   4
-#&gt; 5   -19.72321 -33.57778 14.3   56     5   5
-#&gt; 6    28.00000 -33.07810 14.9   66     5   6
-#&gt; 7    23.00000 299.00000  8.6   65     5   7
-#&gt; 8    19.00000  99.00000 13.8   59     5   8
-#&gt; 9     8.00000  19.00000 20.1   61     5   9
-#&gt; 10  -18.51277 194.00000  8.6   69     5  10
-#&gt; 11    7.00000 -21.37719  6.9   74     5  11
-#&gt; 12   16.00000 256.00000  9.7   69     5  12
-#&gt; 13   11.00000 290.00000  9.2   66     5  13
-#&gt; 14   14.00000 274.00000 10.9   68     5  14
-#&gt; 15   18.00000  65.00000 13.2   58     5  15
-#&gt; 16   14.00000 334.00000 11.5   64     5  16
-#&gt; 17   34.00000 307.00000 12.0   66     5  17
-#&gt; 18    6.00000  78.00000 18.4   57     5  18
-#&gt; 19   30.00000 322.00000 11.5   68     5  19
-#&gt; 20   11.00000  44.00000  9.7   62     5  20
-#&gt; 21    1.00000   8.00000  9.7   59     5  21
-#&gt; 22   11.00000 320.00000 16.6   73     5  22
-#&gt; 23    4.00000  25.00000  9.7   61     5  23
-#&gt; 24   32.00000  92.00000 12.0   61     5  24
-#&gt; 25  -17.81863  66.00000 16.6   57     5  25
-#&gt; 26  -19.43853 266.00000 14.9   58     5  26
-#&gt; 27  -15.14310 -24.60954  8.0   57     5  27
-#&gt; 28   23.00000  13.00000 12.0   67     5  28
-#&gt; 29   45.00000 252.00000 14.9   81     5  29
-#&gt; 30  115.00000 223.00000  5.7   79     5  30
-#&gt; 31   37.00000 279.00000  7.4   76     5  31
-#&gt; 32  -16.17315 286.00000  8.6   78     6   1
-#&gt; 33  -14.65883 287.00000  9.7   74     6   2
-#&gt; 34  -17.85609 242.00000 16.1   67     6   3
-#&gt; 35  -13.29299 186.00000  9.2   84     6   4
-#&gt; 36  -16.16323 220.00000  8.6   85     6   5
-#&gt; 37  -19.60935 264.00000 14.3   79     6   6
-#&gt; 38   29.00000 127.00000  9.7   82     6   7
-#&gt; 39  -19.65780 273.00000  6.9   87     6   8
-#&gt; 40   71.00000 291.00000 13.8   90     6   9
-#&gt; 41   39.00000 323.00000 11.5   87     6  10
-#&gt; 42  -13.40961 259.00000 10.9   93     6  11
-#&gt; 43  -13.53728 250.00000  9.2   92     6  12
-#&gt; 44   23.00000 148.00000  8.0   82     6  13
-#&gt; 45  -19.65993 332.00000 13.8   80     6  14
-#&gt; 46  -16.48342 322.00000 11.5   79     6  15
-#&gt; 47   21.00000 191.00000 14.9   77     6  16
-#&gt; 48   37.00000 284.00000 20.7   72     6  17
-#&gt; 49   20.00000  37.00000  9.2   65     6  18
-#&gt; 50   12.00000 120.00000 11.5   73     6  19
-#&gt; 51   13.00000 137.00000 10.3   76     6  20
-#&gt; 52  -17.17718 150.00000  6.3   77     6  21
-#&gt; 53  -16.74073  59.00000  1.7   76     6  22
-#&gt; 54  -13.65786  91.00000  4.6   76     6  23
-#&gt; 55  -16.78786 250.00000  6.3   76     6  24
-#&gt; 56  -12.30098 135.00000  8.0   75     6  25
-#&gt; 57  -13.33171 127.00000  8.0   78     6  26
-#&gt; 58  -16.77414  47.00000 10.3   73     6  27
-#&gt; 59  -17.08225  98.00000 11.5   80     6  28
-#&gt; 60  -15.98818  31.00000 14.9   77     6  29
-#&gt; 61  -19.17558 138.00000  8.0   83     6  30
-#&gt; 62  135.00000 269.00000  4.1   84     7   1
-#&gt; 63   49.00000 248.00000  9.2   85     7   2
-#&gt; 64   32.00000 236.00000  9.2   81     7   3
-#&gt; 65  -14.27138 101.00000 10.9   84     7   4
-#&gt; 66   64.00000 175.00000  4.6   83     7   5
-#&gt; 67   40.00000 314.00000 10.9   83     7   6
-#&gt; 68   77.00000 276.00000  5.1   88     7   7
-#&gt; 69   97.00000 267.00000  6.3   92     7   8
-#&gt; 70   97.00000 272.00000  5.7   92     7   9
-#&gt; 71   85.00000 175.00000  7.4   89     7  10
-#&gt; 72  -13.51764 139.00000  8.6   82     7  11
-#&gt; 73   10.00000 264.00000 14.3   73     7  12
-#&gt; 74   27.00000 175.00000 14.9   81     7  13
-#&gt; 75  -13.48998 291.00000 14.9   91     7  14
-#&gt; 76    7.00000  48.00000 14.3   80     7  15
-#&gt; 77   48.00000 260.00000  6.9   81     7  16
-#&gt; 78   35.00000 274.00000 10.3   82     7  17
-#&gt; 79   61.00000 285.00000  6.3   84     7  18
-#&gt; 80   79.00000 187.00000  5.1   87     7  19
-#&gt; 81   63.00000 220.00000 11.5   85     7  20
-#&gt; 82   16.00000   7.00000  6.9   74     7  21
-#&gt; 83  -16.92150 258.00000  9.7   81     7  22
-#&gt; 84  -16.60335 295.00000 11.5   82     7  23
-#&gt; 85   80.00000 294.00000  8.6   86     7  24
-#&gt; 86  108.00000 223.00000  8.0   85     7  25
-#&gt; 87   20.00000  81.00000  8.6   82     7  26
-#&gt; 88   52.00000  82.00000 12.0   86     7  27
-#&gt; 89   82.00000 213.00000  7.4   88     7  28
-#&gt; 90   50.00000 275.00000  7.4   86     7  29
-#&gt; 91   64.00000 253.00000  7.4   83     7  30
-#&gt; 92   59.00000 254.00000  9.2   81     7  31
-#&gt; 93   39.00000  83.00000  6.9   81     8   1
-#&gt; 94    9.00000  24.00000 13.8   81     8   2
-#&gt; 95   16.00000  77.00000  7.4   82     8   3
-#&gt; 96   78.00000 -30.94374  6.9   86     8   4
-#&gt; 97   35.00000 -33.38707  7.4   85     8   5
-#&gt; 98   66.00000 -21.48980  4.6   87     8   6
-#&gt; 99  122.00000 255.00000  4.0   89     8   7
-#&gt; 100  89.00000 229.00000 10.3   90     8   8
-#&gt; 101 110.00000 207.00000  8.0   90     8   9
-#&gt; 102 -14.78907 222.00000  8.6   92     8  10
-#&gt; 103 -16.19151 137.00000 11.5   86     8  11
-#&gt; 104  44.00000 192.00000 11.5   86     8  12
-#&gt; 105  28.00000 273.00000 11.5   82     8  13
-#&gt; 106  65.00000 157.00000  9.7   80     8  14
-#&gt; 107 -19.73591  64.00000 11.5   79     8  15
-#&gt; 108  22.00000  71.00000 10.3   77     8  16
-#&gt; 109  59.00000  51.00000  6.3   79     8  17
-#&gt; 110  23.00000 115.00000  7.4   76     8  18
-#&gt; 111  31.00000 244.00000 10.9   78     8  19
-#&gt; 112  44.00000 190.00000 10.3   78     8  20
-#&gt; 113  21.00000 259.00000 15.5   77     8  21
-#&gt; 114   9.00000  36.00000 14.3   72     8  22
-#&gt; 115 -18.92235 255.00000 12.6   75     8  23
-#&gt; 116  45.00000 212.00000  9.7   79     8  24
-#&gt; 117 168.00000 238.00000  3.4   81     8  25
-#&gt; 118  73.00000 215.00000  8.0   86     8  26
-#&gt; 119 -14.86296 153.00000  5.7   88     8  27
-#&gt; 120  76.00000 203.00000  9.7   97     8  28
-#&gt; 121 118.00000 225.00000  2.3   94     8  29
-#&gt; 122  84.00000 237.00000  6.3   96     8  30
-#&gt; 123  85.00000 188.00000  6.3   94     8  31
-#&gt; 124  96.00000 167.00000  6.9   91     9   1
-#&gt; 125  78.00000 197.00000  5.1   92     9   2
-#&gt; 126  73.00000 183.00000  2.8   93     9   3
-#&gt; 127  91.00000 189.00000  4.6   93     9   4
-#&gt; 128  47.00000  95.00000  7.4   87     9   5
-#&gt; 129  32.00000  92.00000 15.5   84     9   6
-#&gt; 130  20.00000 252.00000 10.9   80     9   7
-#&gt; 131  23.00000 220.00000 10.3   78     9   8
-#&gt; 132  21.00000 230.00000 10.9   75     9   9
-#&gt; 133  24.00000 259.00000  9.7   73     9  10
-#&gt; 134  44.00000 236.00000 14.9   81     9  11
-#&gt; 135  21.00000 259.00000 15.5   76     9  12
-#&gt; 136  28.00000 238.00000  6.3   77     9  13
-#&gt; 137   9.00000  24.00000 10.9   71     9  14
-#&gt; 138  13.00000 112.00000 11.5   71     9  15
-#&gt; 139  46.00000 237.00000  6.9   78     9  16
-#&gt; 140  18.00000 224.00000 13.8   67     9  17
-#&gt; 141  13.00000  27.00000 10.3   76     9  18
-#&gt; 142  24.00000 238.00000 10.3   68     9  19
-#&gt; 143  16.00000 201.00000  8.0   82     9  20
-#&gt; 144  13.00000 238.00000 12.6   64     9  21
-#&gt; 145  23.00000  14.00000  9.2   71     9  22
-#&gt; 146  36.00000 139.00000 10.3   81     9  23
-#&gt; 147   7.00000  49.00000 10.3   69     9  24
-#&gt; 148  14.00000  20.00000 16.6   63     9  25
-#&gt; 149  30.00000 193.00000  6.9   70     9  26
-#&gt; 150 -14.83089 145.00000 13.2   77     9  27
-#&gt; 151  14.00000 191.00000 14.3   75     9  28
-#&gt; 152  18.00000 131.00000  8.0   76     9  29
-#&gt; 153  20.00000 223.00000 11.5   68     9  30</div><div class='input'>
-
-</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
-      <li><a href="#arguments">Arguments</a></li>
-      
-      <li><a href="#value">Value</a></li>
-      
-      <li><a href="#examples">Examples</a></li>
-    </ul>
-
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-  <p>Developed by Nicholas Tierney, Di Cook, Miles McBain, Colin Fay.</p>
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diff --git a/docs/reference/impute_shift_if.html b/docs/reference/impute_shift_if.html
deleted file mode 100644
index 41c378d3..00000000
--- a/docs/reference/impute_shift_if.html
+++ /dev/null
@@ -1,330 +0,0 @@
-<!-- Generated by pkgdown: do not edit by hand -->
-<!DOCTYPE html>
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-
-<meta property="og:description" content="impute_shift operates on all variables. To only impute variables
-that satisfy a specific condition, use the scoped variants,
-impute_shift_at, and impute_shift_if." />
-<meta name="twitter:card" content="summary" />
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-  <div class="col-md-9 contents">
-    <div class="page-header">
-    <h1>Scoped variants of <code>impute_shift</code></h1>
-    <small class="dont-index">Source: <a href='https://github.com/njtierney/naniar/blob/master/R/impute_shift.R'><code>R/impute_shift.R</code></a></small>
-    <div class="hidden name"><code>impute_shift_if.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    
-    <p><code>impute_shift</code> operates on all variables. To only impute variables
-that satisfy a specific condition, use the scoped variants,
-<code>impute_shift_at</code>, and <code>impute_shift_if</code>.</p>
-    
-    </div>
-
-    <pre class="usage"><span class='fu'>impute_shift_if</span>(<span class='no'>.tbl</span>, <span class='no'>.predicate</span>, <span class='no'>...</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>.tbl</th>
-      <td><p>data.frame</p></td>
-    </tr>
-    <tr>
-      <th>.predicate</th>
-      <td><p>A predicate function (such as is.numeric)</p></td>
-    </tr>
-    <tr>
-      <th>...</th>
-      <td><p>extra arguments</p></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>an dataset with values imputed</p>
-    
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'>
-<span class='no'>airquality</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'>impute_shift_if</span>(<span class='kw'>.predicate</span> <span class='kw'>=</span> <span class='no'>is.numeric</span>)</div><div class='output co'>#&gt;         Ozone   Solar.R Wind Temp Month Day
-#&gt; 1    41.00000 190.00000  7.4   67     5   1
-#&gt; 2    36.00000 118.00000  8.0   72     5   2
-#&gt; 3    12.00000 149.00000 12.6   74     5   3
-#&gt; 4    18.00000 313.00000 11.5   62     5   4
-#&gt; 5   -19.72321 -33.57778 14.3   56     5   5
-#&gt; 6    28.00000 -33.07810 14.9   66     5   6
-#&gt; 7    23.00000 299.00000  8.6   65     5   7
-#&gt; 8    19.00000  99.00000 13.8   59     5   8
-#&gt; 9     8.00000  19.00000 20.1   61     5   9
-#&gt; 10  -18.51277 194.00000  8.6   69     5  10
-#&gt; 11    7.00000 -21.37719  6.9   74     5  11
-#&gt; 12   16.00000 256.00000  9.7   69     5  12
-#&gt; 13   11.00000 290.00000  9.2   66     5  13
-#&gt; 14   14.00000 274.00000 10.9   68     5  14
-#&gt; 15   18.00000  65.00000 13.2   58     5  15
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-</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
-      <li><a href="#arguments">Arguments</a></li>
-      
-      <li><a href="#value">Value</a></li>
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-    </ul>
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diff --git a/docs/reference/index.html b/docs/reference/index.html
deleted file mode 100644
index 364953d6..00000000
--- a/docs/reference/index.html
+++ /dev/null
@@ -1,715 +0,0 @@
-<!DOCTYPE html>
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-      <img src="../logo.png" class="logo" alt=""><h1>Function reference</h1>
-    </div>
-
-    <div class="section level2">
-      <h2 id="data-structures-for-missing-data">Data structures for missing data<a class="anchor" aria-label="anchor" href="#data-structures-for-missing-data"></a></h2>
-      
-      <p class="section-desc"></p><p>Creation and Manipulation of Shadow Matrices</p>
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-      
-      
-
-      <dl><dt>
-          
-          <code><a href="as_shadow.html">as_shadow()</a></code> 
-        </dt>
-        <dd>Create shadows</dd>
-      </dl><dl><dt>
-          
-          <code><a href="as_shadow_upset.html">as_shadow_upset()</a></code> 
-        </dt>
-        <dd>Convert data into shadow format for doing an upset plot</dd>
-      </dl><dl><dt>
-          
-          <code><a href="bind_shadow.html">bind_shadow()</a></code> 
-        </dt>
-        <dd>Bind a shadow dataframe to original data</dd>
-      </dl><dl><dt>
-          
-          <code><a href="nabular.html">nabular()</a></code> 
-        </dt>
-        <dd>Convert data into nabular form by binding shade to it</dd>
-      </dl><dl><dt>
-          
-          <code><a href="gather_shadow.html">gather_shadow()</a></code> 
-        </dt>
-        <dd>Long form representation of a shadow matrix</dd>
-      </dl><dl><dt>
-          
-          <code><a href="shade.html">shade()</a></code> 
-        </dt>
-        <dd>Create new levels of missing</dd>
-      </dl><dl><dt>
-          
-          <code><a href="shadow_long.html">shadow_long()</a></code> 
-        </dt>
-        <dd>Reshape shadow data into a long format</dd>
-      </dl><dl><dt>
-          
-          <code><a href="unbinders.html">unbind_shadow()</a></code> <code><a href="unbinders.html">unbind_data()</a></code> 
-        </dt>
-        <dd>Unbind (remove) shadow from data, and vice versa</dd>
-      </dl><dl><dt>
-          
-          <code><a href="shadow_shift.html">shadow_shift()</a></code> 
-        </dt>
-        <dd>Shift missing values to facilitate missing data exploration/visualisation</dd>
-      </dl><dl><dt>
-          
-          <code><a href="shadow_shift.numeric.html">shadow_shift(<i>&lt;numeric&gt;</i>)</a></code> 
-        </dt>
-        <dd>Shift (impute) numeric values for graphical exploration</dd>
-      </dl></div><div class="section level2">
-      <h2 id="create-special-missing-values">Create special missing values<a class="anchor" aria-label="anchor" href="#create-special-missing-values"></a></h2>
-      
-      <p class="section-desc"></p><p>Create special missing values so that they don’t get lost!</p>
-
-      
-    </div><div id="" class="section level2">
-      
-      
-      
-
-      <dl><dt>
-          
-          <code><a href="recode_shadow.html">recode_shadow()</a></code> 
-        </dt>
-        <dd>Add special missing values to the shadow matrix</dd>
-      </dl></div><div class="section level2">
-      <h2 id="visualisation">Visualisation<a class="anchor" aria-label="anchor" href="#visualisation"></a></h2>
-      
-      <p class="section-desc"></p><p>Visualise missing data</p>
-
-      
-    </div><div id="" class="section level2">
-      
-      
-      
-
-      <dl><dt>
-          
-          <code><a href="geom_miss_point.html">geom_miss_point()</a></code> 
-        </dt>
-        <dd>geom_miss_point</dd>
-      </dl><dl><dt>
-          
-          <code><a href="stat_miss_point.html">stat_miss_point()</a></code> 
-        </dt>
-        <dd>stat_miss_point</dd>
-      </dl><dl><dt>
-          
-          <code><a href="gg_miss_case.html">gg_miss_case()</a></code> 
-        </dt>
-        <dd>Plot the number of missings per case (row)</dd>
-      </dl><dl><dt>
-          
-          <code><a href="gg_miss_case_cumsum.html">gg_miss_case_cumsum()</a></code> 
-        </dt>
-        <dd>Plot of cumulative sum of missing for cases</dd>
-      </dl><dl><dt>
-          
-          <code><a href="gg_miss_fct.html">gg_miss_fct()</a></code> 
-        </dt>
-        <dd>Plot the number of missings for each variable, broken down by a factor</dd>
-      </dl><dl><dt>
-          
-          <code><a href="gg_miss_span.html">gg_miss_span()</a></code> 
-        </dt>
-        <dd>Plot the number of missings in a given repeating span</dd>
-      </dl><dl><dt>
-          
-          <code><a href="gg_miss_upset.html">gg_miss_upset()</a></code> 
-        </dt>
-        <dd>Plot the pattern of missingness using an upset plot.</dd>
-      </dl><dl><dt>
-          
-          <code><a href="gg_miss_var.html">gg_miss_var()</a></code> 
-        </dt>
-        <dd>Plot the number of missings for each variable</dd>
-      </dl><dl><dt>
-          
-          <code><a href="gg_miss_var_cumsum.html">gg_miss_var_cumsum()</a></code> 
-        </dt>
-        <dd>Plot of cumulative sum of missing value for each variable</dd>
-      </dl><dl><dt>
-          
-          <code><a href="gg_miss_which.html">gg_miss_which()</a></code> 
-        </dt>
-        <dd>Plot which variables contain a missing value</dd>
-      </dl><dl><dt>
-          
-          <code><a href="reexports.html">reexports</a></code> <code><a href="reexports.html">vis_miss</a></code> <code><a href="reexports.html">%&gt;%</a></code> <code><a href="reexports.html">is_na</a></code> <code><a href="reexports.html">are_na</a></code> 
-        </dt>
-        <dd>Objects exported from other packages</dd>
-      </dl></div><div class="section level2">
-      <h2 id="numerical-summaries">Numerical Summaries<a class="anchor" aria-label="anchor" href="#numerical-summaries"></a></h2>
-      
-      <p class="section-desc"></p><p>Provide tidy data frame summaries of missingness</p>
-
-      
-    </div><div id="" class="section level2">
-      
-      
-      
-
-      <dl><dt>
-          
-          <code><a href="miss-pct-prop-defunct.html">miss_var_prop()</a></code> <code><a href="miss-pct-prop-defunct.html">complete_var_prop()</a></code> <code><a href="miss-pct-prop-defunct.html">miss_var_pct()</a></code> <code><a href="miss-pct-prop-defunct.html">complete_var_pct()</a></code> <code><a href="miss-pct-prop-defunct.html">miss_case_prop()</a></code> <code><a href="miss-pct-prop-defunct.html">complete_case_prop()</a></code> <code><a href="miss-pct-prop-defunct.html">miss_case_pct()</a></code> <code><a href="miss-pct-prop-defunct.html">complete_case_pct()</a></code> 
-        </dt>
-        <dd>Proportion of variables containing missings or complete values</dd>
-      </dl><dl><dt>
-          
-          <code><a href="miss_case_cumsum.html">miss_case_cumsum()</a></code> 
-        </dt>
-        <dd>Summarise the missingness in each case</dd>
-      </dl><dl><dt>
-          
-          <code><a href="miss_case_summary.html">miss_case_summary()</a></code> 
-        </dt>
-        <dd>Summarise the missingness in each case</dd>
-      </dl><dl><dt>
-          
-          <code><a href="miss_case_table.html">miss_case_table()</a></code> 
-        </dt>
-        <dd>Tabulate missings in cases.</dd>
-      </dl><dl><dt>
-          
-          <code><a href="miss_prop_summary.html">miss_prop_summary()</a></code> 
-        </dt>
-        <dd>Proportions of missings in data, variables, and cases.</dd>
-      </dl><dl><dt>
-          
-          <code><a href="miss_scan_count.html">miss_scan_count()</a></code> 
-        </dt>
-        <dd>Search and present different kinds of missing values</dd>
-      </dl><dl><dt>
-          
-          <code><a href="miss_summary.html">miss_summary()</a></code> 
-        </dt>
-        <dd>Collate summary measures from naniar into one tibble</dd>
-      </dl><dl><dt>
-          
-          <code><a href="miss_var_cumsum.html">miss_var_cumsum()</a></code> 
-        </dt>
-        <dd>Cumulative sum of the number of missings in each variable</dd>
-      </dl><dl><dt>
-          
-          <code><a href="miss_var_run.html">miss_var_run()</a></code> 
-        </dt>
-        <dd>Find the number of missing and complete values in a single run</dd>
-      </dl><dl><dt>
-          
-          <code><a href="miss_var_span.html">miss_var_span()</a></code> 
-        </dt>
-        <dd>Summarise the number of missings for a given repeating span on a variable</dd>
-      </dl><dl><dt>
-          
-          <code><a href="miss_var_summary.html">miss_var_summary()</a></code> 
-        </dt>
-        <dd>Summarise the missingness in each variable</dd>
-      </dl><dl><dt>
-          
-          <code><a href="miss_var_table.html">miss_var_table()</a></code> 
-        </dt>
-        <dd>Tabulate the missings in the variables</dd>
-      </dl><dl><dt>
-          
-          <code><a href="miss_var_which.html">miss_var_which()</a></code> 
-        </dt>
-        <dd>Which variables contain missing values?</dd>
-      </dl></div><div class="section level2">
-      <h2 id="handy-helpers">Handy helpers<a class="anchor" aria-label="anchor" href="#handy-helpers"></a></h2>
-      
-      <p class="section-desc"></p><p>Handy helpers</p>
-
-      
-    </div><div id="" class="section level2">
-      
-      
-      
-
-      <dl><dt>
-          
-          <code><a href="n-var-case-complete.html">n_var_complete()</a></code> <code><a href="n-var-case-complete.html">n_case_complete()</a></code> 
-        </dt>
-        <dd>The number of variables with complete values</dd>
-      </dl><dl><dt>
-          
-          <code><a href="n-var-case-miss.html">n_var_miss()</a></code> <code><a href="n-var-case-miss.html">n_case_miss()</a></code> 
-        </dt>
-        <dd>The number of variables or cases with missing values</dd>
-      </dl><dl><dt>
-          
-          <code><a href="n_complete.html">n_complete()</a></code> 
-        </dt>
-        <dd>Return the number of complete values</dd>
-      </dl><dl><dt>
-          
-          <code><a href="n_complete_row.html">n_complete_row()</a></code> 
-        </dt>
-        <dd>Return a vector of the number of complete values in each row</dd>
-      </dl><dl><dt>
-          
-          <code><a href="n_miss.html">n_miss()</a></code> 
-        </dt>
-        <dd>Return the number of missing values</dd>
-      </dl><dl><dt>
-          
-          <code><a href="n_miss_row.html">n_miss_row()</a></code> 
-        </dt>
-        <dd>Return a vector of the number of missing values in each row</dd>
-      </dl><dl><dt>
-          
-          <code><a href="prop-miss-complete-case.html">prop_miss_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_complete_case()</a></code> 
-        </dt>
-        <dd>Proportion of cases that contain a missing or complete values.</dd>
-      </dl><dl><dt>
-          
-          <code><a href="prop-miss-complete-var.html">prop_miss_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_complete_var()</a></code> 
-        </dt>
-        <dd>Proportion of variables containing missings or complete values</dd>
-      </dl><dl><dt>
-          
-          <code><a href="prop_complete.html">prop_complete()</a></code> 
-        </dt>
-        <dd>Return the proportion of complete values</dd>
-      </dl><dl><dt>
-          
-          <code><a href="prop_complete_row.html">prop_complete_row()</a></code> 
-        </dt>
-        <dd>Return a vector of the proportion of missing values in each row</dd>
-      </dl><dl><dt>
-          
-          <code><a href="prop_miss.html">prop_miss()</a></code> 
-        </dt>
-        <dd>Return the proportion of missing values</dd>
-      </dl><dl><dt>
-          
-          <code><a href="prop_miss_row.html">prop_miss_row()</a></code> 
-        </dt>
-        <dd>Return a vector of the proportion of missing values in each row</dd>
-      </dl><dl><dt>
-          
-          <code><a href="pct-miss-complete-case.html">pct_miss_case()</a></code> <code><a href="pct-miss-complete-case.html">pct_complete_case()</a></code> 
-        </dt>
-        <dd>Percentage of cases that contain a missing or complete values.</dd>
-      </dl><dl><dt>
-          
-          <code><a href="pct-miss-complete-var.html">pct_miss_var()</a></code> <code><a href="pct-miss-complete-var.html">pct_complete_var()</a></code> 
-        </dt>
-        <dd>Percentage of variables containing missings or complete values</dd>
-      </dl><dl><dt>
-          
-          <code><a href="pct_complete.html">pct_complete()</a></code> 
-        </dt>
-        <dd>Return the percent of complete values</dd>
-      </dl><dl><dt>
-          
-          <code><a href="pct_miss.html">pct_miss()</a></code> 
-        </dt>
-        <dd>Return the percent of missing values</dd>
-      </dl><dl><dt>
-          
-          <code><a href="all-is-miss-complete.html">all_na()</a></code> <code><a href="all-is-miss-complete.html">all_miss()</a></code> <code><a href="all-is-miss-complete.html">all_complete()</a></code> 
-        </dt>
-        <dd>Identify if all values are missing or complete</dd>
-      </dl><dl><dt>
-          
-          <code><a href="any-na.html">any_na()</a></code> <code><a href="any-na.html">any_miss()</a></code> <code><a href="any-na.html">any_complete()</a></code> 
-        </dt>
-        <dd>Identify if there are any missing or complete values</dd>
-      </dl><dl><dt>
-          
-          <code><a href="any_row_miss.html">any_row_miss()</a></code> 
-        </dt>
-        <dd>Helper function to determine whether there are any missings</dd>
-      </dl><dl><dt>
-          
-          <code><a href="is_shade.html">is_shade()</a></code> <code><a href="is_shade.html">are_shade()</a></code> <code><a href="is_shade.html">any_shade()</a></code> 
-        </dt>
-        <dd>Detect if this is a shade</dd>
-      </dl><dl><dt>
-          
-          <code><a href="which_are_shade.html">which_are_shade()</a></code> 
-        </dt>
-        <dd>Which variables are shades?</dd>
-      </dl><dl><dt>
-          
-          <code><a href="common_na_numbers.html">common_na_numbers</a></code> 
-        </dt>
-        <dd>Common number values for NA</dd>
-      </dl><dl><dt>
-          
-          <code><a href="common_na_strings.html">common_na_strings</a></code> 
-        </dt>
-        <dd>Common string values for NA</dd>
-      </dl></div><div class="section level2">
-      <h2 id="add-columns">Add columns<a class="anchor" aria-label="anchor" href="#add-columns"></a></h2>
-      
-      <p class="section-desc"></p><p>Add missing data summaries/tool columns</p>
-
-      
-    </div><div id="" class="section level2">
-      
-      
-      
-
-      <dl><dt>
-          
-          <code><a href="add_any_miss.html">add_any_miss()</a></code> 
-        </dt>
-        <dd>Add a column describing presence of any missing values</dd>
-      </dl><dl><dt>
-          
-          <code><a href="add_label_missings.html">add_label_missings()</a></code> 
-        </dt>
-        <dd>Add a column describing if there are any missings in the dataset</dd>
-      </dl><dl><dt>
-          
-          <code><a href="add_label_shadow.html">add_label_shadow()</a></code> 
-        </dt>
-        <dd>Add a column describing whether there is a shadow</dd>
-      </dl><dl><dt>
-          
-          <code><a href="add_miss_cluster.html">add_miss_cluster()</a></code> 
-        </dt>
-        <dd>Add a column that tells us which "missingness cluster" a row belongs to</dd>
-      </dl><dl><dt>
-          
-          <code><a href="add_n_miss.html">add_n_miss()</a></code> 
-        </dt>
-        <dd>Add column containing number of missing data values</dd>
-      </dl><dl><dt>
-          
-          <code><a href="add_prop_miss.html">add_prop_miss()</a></code> 
-        </dt>
-        <dd>Add column containing proportion of missing data values</dd>
-      </dl><dl><dt>
-          
-          <code><a href="add_shadow.html">add_shadow()</a></code> 
-        </dt>
-        <dd>Add a shadow column to dataframe</dd>
-      </dl><dl><dt>
-          
-          <code><a href="add_shadow_shift.html">add_shadow_shift()</a></code> 
-        </dt>
-        <dd>Add a shadow shifted column to a dataset</dd>
-      </dl><dl><dt>
-          
-          <code><a href="add_span_counter.html">add_span_counter()</a></code> 
-        </dt>
-        <dd>Add a counter variable for a span of dataframe</dd>
-      </dl></div><div class="section level2">
-      <h2 id="replacing-values-with-and-to-na">Replacing values with and to NA<a class="anchor" aria-label="anchor" href="#replacing-values-with-and-to-na"></a></h2>
-      
-      <p class="section-desc"></p><p>Functions to help replace certain values with NA, which includes scoped variants (_at, _if, _all) that take formulas for flexible approachs</p>
-
-      
-    </div><div id="" class="section level2">
-      
-      
-      
-
-      <dl><dt>
-          
-          <code><a href="replace_with_na.html">replace_with_na()</a></code> 
-        </dt>
-        <dd>Replace values with missings</dd>
-      </dl><dl><dt>
-          
-          <code><a href="replace_with_na_all.html">replace_with_na_all()</a></code> 
-        </dt>
-        <dd>Replace all values with NA where a certain condition is met</dd>
-      </dl><dl><dt>
-          
-          <code><a href="replace_with_na_at.html">replace_with_na_at()</a></code> 
-        </dt>
-        <dd>Replace specified variables with NA where a certain condition is met</dd>
-      </dl><dl><dt>
-          
-          <code><a href="replace_with_na_if.html">replace_with_na_if()</a></code> 
-        </dt>
-        <dd>Replace values with NA based on some condition, for variables that meet some predicate</dd>
-      </dl><dl><dt>
-          
-          <code><a href="replace_to_na.html">replace_to_na()</a></code> 
-        </dt>
-        <dd>Replace values with missings</dd>
-      </dl></div><div class="section level2">
-      <h2 id="imputation-helpers">Imputation helpers<a class="anchor" aria-label="anchor" href="#imputation-helpers"></a></h2>
-      
-      <p class="section-desc"></p><p>Simple imputation methods for exploring visualisation and missingness structure</p>
-
-      
-    </div><div id="" class="section level2">
-      
-      
-      
-
-      <dl><dt>
-          
-          <code><a href="impute_below.html">impute_below()</a></code> 
-        </dt>
-        <dd>Impute data with values shifted 10 percent below range.</dd>
-      </dl><dl><dt>
-          
-          <code><a href="impute_below_all.html">impute_below_all()</a></code> 
-        </dt>
-        <dd>Impute data with values shifted 10 percent below range.</dd>
-      </dl><dl><dt>
-          
-          <code><a href="impute_below_at.html">impute_below_at()</a></code> 
-        </dt>
-        <dd>Scoped variants of <code>impute_below</code></dd>
-      </dl><dl><dt>
-          
-          <code><a href="impute_below_if.html">impute_below_if()</a></code> 
-        </dt>
-        <dd>Scoped variants of <code>impute_below</code></dd>
-      </dl><dl><dt>
-          
-          <code><a href="impute_mean.html">impute_mean()</a></code> 
-        </dt>
-        <dd>Impute the mean value into a vector with missing values</dd>
-      </dl><dl><dt>
-          
-          <code><a href="impute_median.html">impute_median()</a></code> 
-        </dt>
-        <dd>Impute the median value into a vector with missing values</dd>
-      </dl><dl><dt>
-          
-          <code><a href="scoped-impute_mean.html">impute_mean_all()</a></code> <code><a href="scoped-impute_mean.html">impute_mean_at()</a></code> <code><a href="scoped-impute_mean.html">impute_mean_if()</a></code> 
-        </dt>
-        <dd>Scoped variants of <code>impute_mean</code></dd>
-      </dl><dl><dt>
-          
-          <code><a href="scoped-impute_median.html">impute_median_all()</a></code> <code><a href="scoped-impute_median.html">impute_median_at()</a></code> <code><a href="scoped-impute_median.html">impute_median_if()</a></code> 
-        </dt>
-        <dd>Scoped variants of <code>impute_median</code></dd>
-      </dl><dl><dt>
-          
-          <code><a href="set-prop-n-miss.html">set_prop_miss()</a></code> <code><a href="set-prop-n-miss.html">set_n_miss()</a></code> 
-        </dt>
-        <dd>Set a proportion or number of missing values</dd>
-      </dl></div><div class="section level2">
-      <h2 id="package-title-details">Package title details<a class="anchor" aria-label="anchor" href="#package-title-details"></a></h2>
-      
-      <p class="section-desc"></p><p>Details of the package naniar</p>
-
-      
-    </div><div id="" class="section level2">
-      
-      
-      
-
-      <dl><dt>
-          
-          <code><a href="naniar.html">naniar</a></code> 
-        </dt>
-        <dd>naniar</dd>
-      </dl></div><div class="section level2">
-      <h2 id="cast-shadows">Cast Shadows<a class="anchor" aria-label="anchor" href="#cast-shadows"></a></h2>
-      
-      <p class="section-desc"></p><p>Add shadow information to the dataframe while reducing it to the variables of interest</p>
-
-      
-    </div><div id="" class="section level2">
-      
-      
-      
-
-      <dl><dt>
-          
-          <code><a href="cast_shadow.html">cast_shadow()</a></code> 
-        </dt>
-        <dd>Add a shadow column to a dataset</dd>
-      </dl><dl><dt>
-          
-          <code><a href="cast_shadow_shift.html">cast_shadow_shift()</a></code> 
-        </dt>
-        <dd>Add a shadow and a shadow_shift column to a dataset</dd>
-      </dl><dl><dt>
-          
-          <code><a href="cast_shadow_shift_label.html">cast_shadow_shift_label()</a></code> 
-        </dt>
-        <dd>Add a shadow column and a shadow shifted column to a dataset</dd>
-      </dl></div><div class="section level2">
-      <h2 id="misc-helpers">Misc helpers<a class="anchor" aria-label="anchor" href="#misc-helpers"></a></h2>
-      
-      <p class="section-desc"></p><p>Misc helpers</p>
-
-      
-    </div><div id="" class="section level2">
-      
-      
-      
-
-      <dl><dt>
-          
-          <code><a href="label_miss_1d.html">label_miss_1d()</a></code> 
-        </dt>
-        <dd>Label a missing from one column</dd>
-      </dl><dl><dt>
-          
-          <code><a href="label_miss_2d.html">label_miss_2d()</a></code> 
-        </dt>
-        <dd>label_miss_2d</dd>
-      </dl><dl><dt>
-          
-          <code><a href="label_missings.html">label_missings()</a></code> 
-        </dt>
-        <dd>Is there a missing value in the row of a dataframe?</dd>
-      </dl><dl><dt>
-          
-          <code><a href="where_na.html">where_na()</a></code> 
-        </dt>
-        <dd>Which rows and cols contain missings?</dd>
-      </dl><dl><dt>
-          
-          <code><a href="which_na.html">which_na()</a></code> 
-        </dt>
-        <dd>Which elements contain missings?</dd>
-      </dl><dl><dt>
-          
-          <code><a href="where.html">.where()</a></code> 
-        </dt>
-        <dd>Split a call into two components with a useful verb name</dd>
-      </dl></div><div class="section level2">
-      <h2 id="data-sources">Data Sources<a class="anchor" aria-label="anchor" href="#data-sources"></a></h2>
-      
-      <p class="section-desc"></p><p>For practice and example usecases in naniar</p>
-
-      
-    </div><div id="" class="section level2">
-      
-      
-      
-
-      <dl><dt>
-          
-          <code><a href="oceanbuoys.html">oceanbuoys</a></code> 
-        </dt>
-        <dd>West Pacific Tropical Atmosphere Ocean Data, 1993 &amp; 1997.</dd>
-      </dl><dl><dt>
-          
-          <code><a href="pedestrian.html">pedestrian</a></code> 
-        </dt>
-        <dd>Pedestrian count information around Melbourne for 2016</dd>
-      </dl><dl><dt>
-          
-          <code><a href="riskfactors.html">riskfactors</a></code> 
-        </dt>
-        <dd>The Behavioral Risk Factor Surveillance System (BRFSS) Survey
-Data, 2009.</dd>
-      </dl></div><div class="section level2">
-      <h2 id="little-s-mcar-test">Little’s MCAR test<a class="anchor" aria-label="anchor" href="#little-s-mcar-test"></a></h2>
-      
-      <p class="section-desc"></p><p>For performing Little’s MCAR test</p>
-
-      
-    </div><div id="" class="section level2">
-      
-      
-      
-
-      <dl><dt>
-          
-          <code><a href="mcar_test.html">mcar_test()</a></code> 
-        </dt>
-        <dd>Little's missing completely at random (MCAR) test</dd>
-      </dl></div><div class="section level2">
-      <h2 id="ggplot-extensions">ggplot2 extensions<a class="anchor" aria-label="anchor" href="#ggplot-extensions"></a></h2>
-      
-      <p class="section-desc"></p><p>Custom ggplot geoms built to extend ggplot for missing values</p>
-
-      
-    </div><div id="" class="section level2">
-      
-      
-      
-
-      <dl><dt>
-          
-          <code><a href="naniar-ggproto.html">StatMissPoint</a></code> 
-        </dt>
-        <dd>naniar-ggproto</dd>
-      </dl></div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
-
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-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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-      <img src="../logo.png" class="logo" alt=""><h1>Detect if this is a shade</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/shade.R" class="external-link"><code>R/shade.R</code></a></small>
-      <div class="d-none name"><code>is_shade.Rd</code></div>
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-    <p>This tells us if this column is a shade</p>
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-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">is_shade</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">are_shade</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">any_shade</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span></code></pre></div>
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-
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-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
-<dd><p>a vector you want to test if is a shade</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>logical - is this a shade?</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">xs</span> <span class="op">&lt;-</span> <span class="fu"><a href="shade.html">shade</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="cn">NA</span>, <span class="fl">1</span>, <span class="fl">2</span>, <span class="st">"3"</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">is_shade</span><span class="op">(</span><span class="va">xs</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] TRUE</span>
-<span class="r-in"><span><span class="fu">are_shade</span><span class="op">(</span><span class="va">xs</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] TRUE TRUE TRUE TRUE</span>
-<span class="r-in"><span><span class="fu">any_shade</span><span class="op">(</span><span class="va">xs</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] TRUE</span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">aq_s</span> <span class="op">&lt;-</span> <span class="fu"><a href="as_shadow.html">as_shadow</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">is_shade</span><span class="op">(</span><span class="va">aq_s</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] FALSE</span>
-<span class="r-in"><span><span class="fu">are_shade</span><span class="op">(</span><span class="va">aq_s</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   Ozone_NA Solar.R_NA    Wind_NA    Temp_NA   Month_NA     Day_NA </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>       TRUE       TRUE       TRUE       TRUE       TRUE       TRUE </span>
-<span class="r-in"><span><span class="fu">any_shade</span><span class="op">(</span><span class="va">aq_s</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] TRUE</span>
-<span class="r-in"><span><span class="fu">any_shade</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] FALSE</span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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-    <h1>Test if input is or are shadow variables</h1>
-    <small class="dont-index">Source: <a href='https://github.com/njtierney/naniar/blob/master/R/shadow-verifiers.R'><code>R/shadow-verifiers.R</code></a></small>
-    <div class="hidden name"><code>is_shadow.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Shadow matrix or "nabular" data is a useful way to store missing data to
-facilitate missing data visualisation. This data can be created using
-<code>bind_shadow</code>. <code>is_shadow</code> tells us if there are any shadow variables.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>is_shadow</span>(<span class='no'>x</span>)
-
-<span class='fu'>is_nabular</span>(<span class='no'>x</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>x</th>
-      <td><p>a vector or data.frame</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>logical vector of length 1</p>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'>
-<span class='no'>aq_sh</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='as_shadow.html'>as_shadow</a></span>(<span class='no'>airquality</span>)
-<span class='no'>aq_bind</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='bind_shadow.html'>bind_shadow</a></span>(<span class='no'>airquality</span>)
-
-<span class='fu'>is_shadow</span>(<span class='no'>aq_sh</span>)</div><div class='output co'>#&gt; [1] TRUE</div><div class='input'><span class='fu'>is_shadow</span>(<span class='no'>airquality</span>)</div><div class='output co'>#&gt; [1] FALSE</div><div class='input'><span class='fu'>is_shadow</span>(<span class='no'>aq_bind</span>)</div><div class='output co'>#&gt; [1] FALSE</div><div class='input'><span class='fu'>is_nabular</span>(<span class='no'>aq_bind</span>)</div><div class='output co'>#&gt; [1] TRUE</div><div class='input'>
-</div></pre>
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diff --git a/docs/reference/label_miss_1d.html b/docs/reference/label_miss_1d.html
deleted file mode 100644
index 49241ef7..00000000
--- a/docs/reference/label_miss_1d.html
+++ /dev/null
@@ -1,149 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Label whether a value is missing in a row of one columns."><title>Label a missing from one column — label_miss_1d • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Label a missing from one column — label_miss_1d"><meta property="og:description" content="Label whether a value is missing in a row of one columns."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/label-miss.R" class="external-link"><code>R/label-miss.R</code></a></small>
-      <div class="d-none name"><code>label_miss_1d.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Label whether a value is missing in a row of one columns.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">label_miss_1d</span><span class="op">(</span><span class="va">x1</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x1</dt>
-<dd><p>a variable of a dataframe</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>a vector indicating whether any of these rows had missing values</p>
-    </div>
-    <div class="section level2">
-    <h2 id="note">Note<a class="anchor" aria-label="anchor" href="#note"></a></h2>
-    <p>can we generalise label_miss to work for any number of variables?</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="add_any_miss.html">add_any_miss()</a></code> <code><a href="add_label_missings.html">add_label_missings()</a></code> <code><a href="add_label_shadow.html">add_label_shadow()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">label_miss_1d</span><span class="op">(</span><span class="va">airquality</span><span class="op">$</span><span class="va">Ozone</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   [1] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   [6] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [11] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [16] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [21] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [26] "Missing"     "Missing"     "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [31] "Not Missing" "Missing"     "Missing"     "Missing"     "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [36] "Missing"     "Missing"     "Not Missing" "Missing"     "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [41] "Not Missing" "Missing"     "Missing"     "Not Missing" "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [46] "Missing"     "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [51] "Not Missing" "Missing"     "Missing"     "Missing"     "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [56] "Missing"     "Missing"     "Missing"     "Missing"     "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [61] "Missing"     "Not Missing" "Not Missing" "Not Missing" "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [66] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [71] "Not Missing" "Missing"     "Not Missing" "Not Missing" "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [76] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [81] "Not Missing" "Not Missing" "Missing"     "Missing"     "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [86] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [91] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [96] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [101] "Not Missing" "Missing"     "Missing"     "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [106] "Not Missing" "Missing"     "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [111] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [116] "Not Missing" "Not Missing" "Not Missing" "Missing"     "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [121] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [126] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [131] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [136] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [141] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [146] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [151] "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/label_miss_2d.html b/docs/reference/label_miss_2d.html
deleted file mode 100644
index a83e5989..00000000
--- a/docs/reference/label_miss_2d.html
+++ /dev/null
@@ -1,145 +0,0 @@
-<!DOCTYPE html>
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-      <img src="../logo.png" class="logo" alt=""><h1>label_miss_2d</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/label-miss.R" class="external-link"><code>R/label-miss.R</code></a></small>
-      <div class="d-none name"><code>label_miss_2d.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Label whether a value is missing in either row of two columns.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">label_miss_2d</span><span class="op">(</span><span class="va">x1</span>, <span class="va">x2</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x1</dt>
-<dd><p>a variable of a dataframe</p></dd>
-
-
-<dt>x2</dt>
-<dd><p>another variable of a dataframe</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>a vector indicating whether any of these rows had missing values</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">label_miss_2d</span><span class="op">(</span><span class="va">airquality</span><span class="op">$</span><span class="va">Ozone</span>, <span class="va">airquality</span><span class="op">$</span><span class="va">Solar.R</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   [1] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   [6] "Missing"     "Not Missing" "Not Missing" "Not Missing" "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [11] "Missing"     "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [16] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [21] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [26] "Missing"     "Missing"     "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [31] "Not Missing" "Missing"     "Missing"     "Missing"     "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [36] "Missing"     "Missing"     "Not Missing" "Missing"     "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [41] "Not Missing" "Missing"     "Missing"     "Not Missing" "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [46] "Missing"     "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [51] "Not Missing" "Missing"     "Missing"     "Missing"     "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [56] "Missing"     "Missing"     "Missing"     "Missing"     "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [61] "Missing"     "Not Missing" "Not Missing" "Not Missing" "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [66] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [71] "Not Missing" "Missing"     "Not Missing" "Not Missing" "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [76] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [81] "Not Missing" "Not Missing" "Missing"     "Missing"     "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [86] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [91] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [96] "Missing"     "Missing"     "Missing"     "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [101] "Not Missing" "Missing"     "Missing"     "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [106] "Not Missing" "Missing"     "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [111] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [116] "Not Missing" "Not Missing" "Not Missing" "Missing"     "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [121] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [126] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [131] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [136] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [141] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [146] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [151] "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/label_missing_1d.html b/docs/reference/label_missing_1d.html
deleted file mode 100644
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--- a/docs/reference/label_missing_1d.html
+++ /dev/null
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-    <h1>label_missing_1d</h1>
-    </div>
-
-    
-    <p>Label whether a value is missing in either row of two columns. At the moment this is a more appealing alternative to miss_cat, which is at this stage a bit complicated.</p>
-    
-
-    <pre class="usage"><span class='fu'>label_missing_1d</span>(<span class='no'>x1</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a> Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>x1</th>
-      <td><p>a variable of a dataframe</p></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>a vector indicating whether any of these rows had missing values</p>
-    
-    <h2 class="hasAnchor" id="note"><a class="anchor" href="#note"></a>Note</h2>
-
-    <p>can we generalise label_missing to work for any number of variables?</p>
-    
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'>
-<span class='fu'>label_missing_1d</span>(<span class='no'>airquality</span>$<span class='no'>Ozone</span>)</div><div class='output co'>#&gt;   [1] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Missing"    
-#&gt;   [6] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Missing"    
-#&gt;  [11] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"
-#&gt;  [16] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"
-#&gt;  [21] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Missing"    
-#&gt;  [26] "Missing"     "Missing"     "Not Missing" "Not Missing" "Not Missing"
-#&gt;  [31] "Not Missing" "Missing"     "Missing"     "Missing"     "Missing"    
-#&gt;  [36] "Missing"     "Missing"     "Not Missing" "Missing"     "Not Missing"
-#&gt;  [41] "Not Missing" "Missing"     "Missing"     "Not Missing" "Missing"    
-#&gt;  [46] "Missing"     "Not Missing" "Not Missing" "Not Missing" "Not Missing"
-#&gt;  [51] "Not Missing" "Missing"     "Missing"     "Missing"     "Missing"    
-#&gt;  [56] "Missing"     "Missing"     "Missing"     "Missing"     "Missing"    
-#&gt;  [61] "Missing"     "Not Missing" "Not Missing" "Not Missing" "Missing"    
-#&gt;  [66] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"
-#&gt;  [71] "Not Missing" "Missing"     "Not Missing" "Not Missing" "Missing"    
-#&gt;  [76] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"
-#&gt;  [81] "Not Missing" "Not Missing" "Missing"     "Missing"     "Not Missing"
-#&gt;  [86] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"
-#&gt;  [91] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"
-#&gt;  [96] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"
-#&gt; [101] "Not Missing" "Missing"     "Missing"     "Not Missing" "Not Missing"
-#&gt; [106] "Not Missing" "Missing"     "Not Missing" "Not Missing" "Not Missing"
-#&gt; [111] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Missing"    
-#&gt; [116] "Not Missing" "Not Missing" "Not Missing" "Missing"     "Not Missing"
-#&gt; [121] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"
-#&gt; [126] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"
-#&gt; [131] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"
-#&gt; [136] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"
-#&gt; [141] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"
-#&gt; [146] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Missing"    
-#&gt; [151] "Not Missing" "Not Missing" "Not Missing"</div><div class='input'>
-</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
-      <li><a href="#arguments">Arguments</a></li>
-      
-      <li><a href="#value">Value</a></li>
-
-      <li><a href="#note">Note</a></li>
-      
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diff --git a/docs/reference/label_missing_2d.html b/docs/reference/label_missing_2d.html
deleted file mode 100644
index 5fd2a9b9..00000000
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+++ /dev/null
@@ -1,186 +0,0 @@
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-
-    
-    <p>Label whether a value is missing in either row of two columns. This is a more appealing alternative to miss_cat, which seems a bit overcomplicated.</p>
-    
-
-    <pre class="usage"><span class='fu'>label_missing_2d</span>(<span class='no'>x1</span>, <span class='no'>x2</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a> Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>x1</th>
-      <td><p>a variable of a dataframe</p></td>
-    </tr>
-    <tr>
-      <th>x2</th>
-      <td><p>another variable of a dataframe</p></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>a vector indicating whether any of these rows had missing values</p>
-    
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'>
-<span class='fu'>label_missing_2d</span>(<span class='no'>airquality</span>$<span class='no'>Ozone</span>, <span class='no'>airquality</span>$<span class='no'>Solar.R</span>)</div><div class='output co'>#&gt;   [1] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Missing"    
-#&gt;   [6] "Missing"     "Not Missing" "Not Missing" "Not Missing" "Missing"    
-#&gt;  [11] "Missing"     "Not Missing" "Not Missing" "Not Missing" "Not Missing"
-#&gt;  [16] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"
-#&gt;  [21] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Missing"    
-#&gt;  [26] "Missing"     "Missing"     "Not Missing" "Not Missing" "Not Missing"
-#&gt;  [31] "Not Missing" "Missing"     "Missing"     "Missing"     "Missing"    
-#&gt;  [36] "Missing"     "Missing"     "Not Missing" "Missing"     "Not Missing"
-#&gt;  [41] "Not Missing" "Missing"     "Missing"     "Not Missing" "Missing"    
-#&gt;  [46] "Missing"     "Not Missing" "Not Missing" "Not Missing" "Not Missing"
-#&gt;  [51] "Not Missing" "Missing"     "Missing"     "Missing"     "Missing"    
-#&gt;  [56] "Missing"     "Missing"     "Missing"     "Missing"     "Missing"    
-#&gt;  [61] "Missing"     "Not Missing" "Not Missing" "Not Missing" "Missing"    
-#&gt;  [66] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"
-#&gt;  [71] "Not Missing" "Missing"     "Not Missing" "Not Missing" "Missing"    
-#&gt;  [76] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"
-#&gt;  [81] "Not Missing" "Not Missing" "Missing"     "Missing"     "Not Missing"
-#&gt;  [86] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"
-#&gt;  [91] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"
-#&gt;  [96] "Missing"     "Missing"     "Missing"     "Not Missing" "Not Missing"
-#&gt; [101] "Not Missing" "Missing"     "Missing"     "Not Missing" "Not Missing"
-#&gt; [106] "Not Missing" "Missing"     "Not Missing" "Not Missing" "Not Missing"
-#&gt; [111] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Missing"    
-#&gt; [116] "Not Missing" "Not Missing" "Not Missing" "Missing"     "Not Missing"
-#&gt; [121] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"
-#&gt; [126] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"
-#&gt; [131] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"
-#&gt; [136] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"
-#&gt; [141] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"
-#&gt; [146] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Missing"    
-#&gt; [151] "Not Missing" "Not Missing" "Not Missing"</div><div class='input'>
-</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
-      <li><a href="#arguments">Arguments</a></li>
-      
-      <li><a href="#value">Value</a></li>
-      
-      <li><a href="#examples">Examples</a></li>
-    </ul>
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diff --git a/docs/reference/label_missings.html b/docs/reference/label_missings.html
deleted file mode 100644
index 985bf534..00000000
--- a/docs/reference/label_missings.html
+++ /dev/null
@@ -1,170 +0,0 @@
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-      <img src="../logo.png" class="logo" alt=""><h1>Is there a missing value in the row of a dataframe?</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/add-cols.R" class="external-link"><code>R/add-cols.R</code></a></small>
-      <div class="d-none name"><code>label_missings.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Creates a character vector describing presence/absence of missing values</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">label_missings</span><span class="op">(</span><span class="va">data</span>, <span class="va">...</span>, missing <span class="op">=</span> <span class="st">"Missing"</span>, complete <span class="op">=</span> <span class="st">"Not Missing"</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>a dataframe or set of vectors of the same length</p></dd>
-
-
-<dt>...</dt>
-<dd><p>extra variable to label</p></dd>
-
-
-<dt>missing</dt>
-<dd><p>character a label for when values are missing - defaults to "Missing"</p></dd>
-
-
-<dt>complete</dt>
-<dd><p>character character a label for when values are complete - defaults to "Not Missing"</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>character vector of "Missing" and "Not Missing".</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="bind_shadow.html">bind_shadow()</a></code> <code><a href="add_any_miss.html">add_any_miss()</a></code> <code><a href="add_label_missings.html">add_label_missings()</a></code> <code><a href="add_label_shadow.html">add_label_shadow()</a></code> <code><a href="add_miss_cluster.html">add_miss_cluster()</a></code> <code><a href="add_n_miss.html">add_n_miss()</a></code> <code><a href="add_prop_miss.html">add_prop_miss()</a></code> <code><a href="add_shadow_shift.html">add_shadow_shift()</a></code> <code><a href="cast_shadow.html">cast_shadow()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">label_missings</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   [1] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   [6] "Missing"     "Not Missing" "Not Missing" "Not Missing" "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [11] "Missing"     "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [16] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [21] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [26] "Missing"     "Missing"     "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [31] "Not Missing" "Missing"     "Missing"     "Missing"     "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [36] "Missing"     "Missing"     "Not Missing" "Missing"     "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [41] "Not Missing" "Missing"     "Missing"     "Not Missing" "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [46] "Missing"     "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [51] "Not Missing" "Missing"     "Missing"     "Missing"     "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [56] "Missing"     "Missing"     "Missing"     "Missing"     "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [61] "Missing"     "Not Missing" "Not Missing" "Not Missing" "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [66] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [71] "Not Missing" "Missing"     "Not Missing" "Not Missing" "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [76] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [81] "Not Missing" "Not Missing" "Missing"     "Missing"     "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [86] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [91] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [96] "Missing"     "Missing"     "Missing"     "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [101] "Not Missing" "Missing"     "Missing"     "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [106] "Not Missing" "Missing"     "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [111] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [116] "Not Missing" "Not Missing" "Not Missing" "Missing"     "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [121] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [126] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [131] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [136] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [141] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [146] "Not Missing" "Not Missing" "Not Missing" "Not Missing" "Missing"    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [151] "Not Missing" "Not Missing" "Not Missing"</span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>is_missing <span class="op">=</span> <span class="fu">label_missings</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>is_missing <span class="op">=</span> <span class="fu">label_missings</span><span class="op">(</span><span class="va">airquality</span>,</span></span>
-<span class="r-in"><span>                                     missing <span class="op">=</span> <span class="st">"definitely missing"</span>,</span></span>
-<span class="r-in"><span>                                     complete <span class="op">=</span> <span class="st">"absolutely complete"</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/label_na.html b/docs/reference/label_na.html
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-    <h1>Give NAs a more meaningful label</h1>
-    </div>
-
-    
-    <p>Returns a binary factor of !NA and NA, where !NA indicates a datum that is
-not missing, and NA indicates missingness. This function is what powers the
-factor levels in <code><a href='as_shadow.html'>as_shadow()</a></code>.</p>
-    
-
-    <pre class="usage"><span class='fu'>label_na</span>(<span class='no'>x</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a> Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>x</th>
-      <td><p>a vector</p></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>a vector of factors containing the labels "!NA" for Not missing and
-"NA" for missing.</p>
-    
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <p>as_shadow</p>
-    
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><span class='co'># NOT RUN {</span>
-<span class='fu'>label_na</span>(<span class='no'>airquality</span>$<span class='no'>Ozone</span>)
-<span class='co'># }</span></pre>
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diff --git a/docs/reference/label_shadow.html b/docs/reference/label_shadow.html
deleted file mode 100644
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-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>data.frame</p></td>
-    </tr>
-    <tr>
-      <th>...</th>
-      <td><p>extra variable to label</p></td>
-    </tr>
-    <tr>
-      <th>missing</th>
-      <td><p>character a label for when values are missing - defaults to "Missing"</p></td>
-    </tr>
-    <tr>
-      <th>complete</th>
-      <td><p>character character a label for when values are complete - defaults to "Not Missing"</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>"Missing" or "Not Missing"</p>
-
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diff --git a/docs/reference/label_shadow_matrix.html b/docs/reference/label_shadow_matrix.html
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-  <div class="col-md-9 contents">
-    <div class="page-header">
-    <h1>Give NAs a more meaningful label</h1>
-    <small class="dont-index">Source: <a href='https://github.com/njtierney/naniar/blob/master/R/label-miss.R'><code>R/label-miss.R</code></a></small>
-    <div class="hidden name"><code>label_shadow_matrix.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    
-    <p>Returns a binary factor of !NA and NA, where !NA indicates a datum that is
-not missing, and NA indicates missingness. This function is what powers the
-factor levels in <code><a href='as_shadow.html'>as_shadow()</a></code>.</p>
-    
-    </div>
-
-    <pre class="usage"><span class='fu'>label_shadow_matrix</span>(<span class='no'>x</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>x</th>
-      <td><p>a vector</p></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>a vector of factors containing the labels "!NA" for Not missing and
-"NA" for missing.</p>
-    
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>as_shadow</p></div>
-    
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><span class='co'># NOT RUN {</span>
-<span class='fu'>label_shadow_matrix</span>(<span class='no'>airquality</span>$<span class='no'>Ozone</span>)
-<span class='co'># }</span></pre>
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diff --git a/docs/reference/miss-complete-case-pct.html b/docs/reference/miss-complete-case-pct.html
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-    <h1>Percentage of cases that contain a missing or complete values.</h1>
-    <small class="dont-index">Source: <a href='https://github.com/njtierney/naniar/blob/master/R/miss-complete-x-pct-prop.R'><code>R/miss-complete-x-pct-prop.R</code></a></small>
-    <div class="hidden name"><code>miss-complete-case-pct.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    
-    <p>Deprecated, please see <code>miss_case_pct()</code> and <code>complete_case_pct()</code>.</p>
-    
-    </div>
-
-    <pre class="usage"><span class='fu'>miss_case_pct</span>(<span class='no'>data</span>)
-
-<span class='fu'>complete_case_pct</span>(<span class='no'>data</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>a dataframe</p></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>numeric the percentage of cases that contain a missing or complete
-value</p>
-    
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p><code><a href='pct-miss-complete-case.html'>pct_miss_case()</a></code> <code><a href='prop-miss-complete-case.html'>prop_miss_case()</a></code> <code><a href='pct-miss-complete-var.html'>pct_miss_var()</a></code> <code><a href='prop-miss-complete-var.html'>prop_miss_var()</a></code> <code><a href='pct-miss-complete-case.html'>pct_complete_case()</a></code> <code><a href='prop-miss-complete-case.html'>prop_complete_case()</a></code> <code><a href='pct-miss-complete-var.html'>pct_complete_var()</a></code> <code><a href='prop-miss-complete-var.html'>prop_complete_var()</a></code> <code><a href='miss_prop_summary.html'>miss_prop_summary()</a></code> <code><a href='miss_case_summary.html'>miss_case_summary()</a></code> <code><a href='miss_case_table.html'>miss_case_table()</a></code> <code><a href='miss_summary.html'>miss_summary()</a></code> <code><a href='miss-complete-var-prop.html'>miss_var_prop()</a></code> <code><a href='miss_var_run.html'>miss_var_run()</a></code> <code><a href='miss_var_span.html'>miss_var_span()</a></code> <code><a href='miss_var_summary.html'>miss_var_summary()</a></code> <code><a href='miss_var_table.html'>miss_var_table()</a></code></p></div>
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-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
-      <li><a href="#arguments">Arguments</a></li>
-      
-      <li><a href="#value">Value</a></li>
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-    <h1>Proportion of cases that contain a missing or complete values.</h1>
-    <small class="dont-index">Source: <a href='https://github.com/njtierney/naniar/blob/master/R/miss-complete-x-pct-prop.R'><code>R/miss-complete-x-pct-prop.R</code></a></small>
-    <div class="hidden name"><code>miss-complete-case-prop.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    
-    <p>Deprecated, please see <code>miss_case_prop()</code> and <code>complete_case_prop()</code>.</p>
-    
-    </div>
-
-    <pre class="usage"><span class='fu'>miss_case_prop</span>(<span class='no'>data</span>)
-
-<span class='fu'>complete_case_prop</span>(<span class='no'>data</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>a dataframe</p></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>numeric the proportion of cases that contain a missing or complete
-value</p>
-    
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p><code><a href='pct-miss-complete-case.html'>pct_miss_case()</a></code> <code><a href='prop-miss-complete-case.html'>prop_miss_case()</a></code> <code><a href='pct-miss-complete-var.html'>pct_miss_var()</a></code> <code><a href='prop-miss-complete-var.html'>prop_miss_var()</a></code> <code><a href='pct-miss-complete-case.html'>pct_complete_case()</a></code> <code><a href='prop-miss-complete-case.html'>prop_complete_case()</a></code> <code><a href='pct-miss-complete-var.html'>pct_complete_var()</a></code> <code><a href='prop-miss-complete-var.html'>prop_complete_var()</a></code> <code><a href='miss_prop_summary.html'>miss_prop_summary()</a></code> <code><a href='miss_case_summary.html'>miss_case_summary()</a></code> <code><a href='miss_case_table.html'>miss_case_table()</a></code> <code><a href='miss_summary.html'>miss_summary()</a></code> <code><a href='miss-complete-var-prop.html'>miss_var_prop()</a></code> <code><a href='miss_var_run.html'>miss_var_run()</a></code> <code><a href='miss_var_span.html'>miss_var_span()</a></code> <code><a href='miss_var_summary.html'>miss_var_summary()</a></code> <code><a href='miss_var_table.html'>miss_var_table()</a></code></p></div>
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-    <h1>Percentage of variables containing missings or complete values</h1>
-    <small class="dont-index">Source: <a href='https://github.com/njtierney/naniar/blob/master/R/miss-complete-x-pct-prop.R'><code>R/miss-complete-x-pct-prop.R</code></a></small>
-    <div class="hidden name"><code>miss-complete-var-pct.Rd</code></div>
-    </div>
-
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-    
-    <p>Deprecated. Please see <code>miss_var_pct()</code> and <code>complete_var_pct()</code>.</p>
-    
-    </div>
-
-    <pre class="usage"><span class='fu'>miss_var_pct</span>(<span class='no'>data</span>)
-
-<span class='fu'>complete_var_pct</span>(<span class='no'>data</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>a dataframe</p></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>numeric the percent of variables that contain missing or complete
-data</p>
-    
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p><code><a href='pct-miss-complete-case.html'>pct_miss_case()</a></code> <code><a href='prop-miss-complete-case.html'>prop_miss_case()</a></code> <code><a href='pct-miss-complete-var.html'>pct_miss_var()</a></code> <code><a href='prop-miss-complete-var.html'>prop_miss_var()</a></code> <code><a href='pct-miss-complete-case.html'>pct_complete_case()</a></code> <code><a href='prop-miss-complete-case.html'>prop_complete_case()</a></code> <code><a href='pct-miss-complete-var.html'>pct_complete_var()</a></code> <code><a href='prop-miss-complete-var.html'>prop_complete_var()</a></code> <code><a href='miss_prop_summary.html'>miss_prop_summary()</a></code> <code><a href='miss_case_summary.html'>miss_case_summary()</a></code> <code><a href='miss_case_table.html'>miss_case_table()</a></code> <code><a href='miss_summary.html'>miss_summary()</a></code> <code><a href='miss-complete-var-prop.html'>miss_var_prop()</a></code> <code><a href='miss_var_run.html'>miss_var_run()</a></code> <code><a href='miss_var_span.html'>miss_var_span()</a></code> <code><a href='miss_var_summary.html'>miss_var_summary()</a></code> <code><a href='miss_var_table.html'>miss_var_table()</a></code></p></div>
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-    <h2>Contents</h2>
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-  <div class="col-md-9 contents">
-    <div class="page-header">
-    <h1>Proportion of variables containing missings or complete values</h1>
-    <small class="dont-index">Source: <a href='https://github.com/njtierney/naniar/blob/master/R/miss-complete-x-pct-prop.R'><code>R/miss-complete-x-pct-prop.R</code></a></small>
-    <div class="hidden name"><code>miss-complete-var-prop.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    
-    <p>Deprecated. Please see <code>miss_var_prop()</code> and <code>complete_var_prop()</code>.</p>
-    
-    </div>
-
-    <pre class="usage"><span class='fu'>miss_var_prop</span>(<span class='no'>data</span>)
-
-<span class='fu'>complete_var_prop</span>(<span class='no'>data</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>a dataframe</p></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>numeric the proportion of variables that contain missing or complete
-data</p>
-    
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p><code><a href='pct-miss-complete-case.html'>pct_miss_case()</a></code> <code><a href='prop-miss-complete-case.html'>prop_miss_case()</a></code> <code><a href='pct-miss-complete-var.html'>pct_miss_var()</a></code> <code><a href='prop-miss-complete-var.html'>prop_miss_var()</a></code> <code><a href='pct-miss-complete-case.html'>pct_complete_case()</a></code> <code><a href='prop-miss-complete-case.html'>prop_complete_case()</a></code> <code><a href='pct-miss-complete-var.html'>pct_complete_var()</a></code> <code><a href='prop-miss-complete-var.html'>prop_complete_var()</a></code> <code><a href='miss_prop_summary.html'>miss_prop_summary()</a></code> <code><a href='miss_case_summary.html'>miss_case_summary()</a></code> <code><a href='miss_case_table.html'>miss_case_table()</a></code> <code><a href='miss_summary.html'>miss_summary()</a></code> <code>miss_var_prop()</code> <code><a href='miss_var_run.html'>miss_var_run()</a></code> <code><a href='miss_var_span.html'>miss_var_span()</a></code> <code><a href='miss_var_summary.html'>miss_var_summary()</a></code> <code><a href='miss_var_table.html'>miss_var_table()</a></code></p></div>
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diff --git a/docs/reference/miss_case_cumsum.html b/docs/reference/miss_case_cumsum.html
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-      <img src="../logo.png" class="logo" alt=""><h1>Summarise the missingness in each case</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/miss-x-cumsum.R" class="external-link"><code>R/miss-x-cumsum.R</code></a></small>
-      <div class="d-none name"><code>miss_case_cumsum.Rd</code></div>
-    </div>
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-    <p>Provide a data.frame containing each case (row), the number and percent of
-missing values in each case.</p>
-    </div>
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-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">miss_case_cumsum</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>a dataframe</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>a tibble containing the number and percent of missing data in each
-case</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">miss_case_cumsum</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>     case n_miss n_miss_cumsum</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>     1      0             0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>     2      0             0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>     3      0             0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>     4      0             0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>     5      2             2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>     6      1             3</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>     7      0             3</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>     8      0             3</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>     9      0             3</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>    10      1             4</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">Month</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu">miss_case_cumsum</span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/miss_case_pct.html b/docs/reference/miss_case_pct.html
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-    
-    <p>Calculate the percentage of cases (rows) that contain a missing value.</p>
-    
-    </div>
-
-    <pre class="usage"><span class='fu'>miss_case_pct</span>(<span class='no'>data</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>a dataframe</p></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>numeric the percentage of cases that contain a missing value</p>
-    
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p><a href='miss_case_prop'>miss_case_prop</a> <code><a href='miss_prop_summary.html'>miss_prop_summary()</a></code> <a href='miss_case_summary'>miss_case_summary</a> <a href='miss_case_table'>miss_case_table</a> <a href='miss_summary'>miss_summary</a> <a href='miss_var_pct'>miss_var_pct</a> <a href='miss_var_prop'>miss_var_prop</a> <a href='miss_var_run'>miss_var_run</a> <a href='miss_var_span'>miss_var_span</a> <a href='miss_var_summary'>miss_var_summary</a> <a href='miss_var_table'>miss_var_table</a></p></div>
-    
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'>
-<span class='fu'>miss_case_pct</span>(<span class='no'>airquality</span>)</div><div class='output co'>#&gt; [1] 27.45098</div><div class='input'>
-</div></pre>
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-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
-      <li><a href="#arguments">Arguments</a></li>
-      
-      <li><a href="#value">Value</a></li>
-
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diff --git a/docs/reference/miss_case_prop.html b/docs/reference/miss_case_prop.html
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-    <small class="dont-index">Source: <a href='https://github.com/njtierney/naniar/blob/master/R/miss-x-pct-prop.R'><code>R/miss-x-pct-prop.R</code></a></small>
-    <div class="hidden name"><code>miss_case_prop.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    
-    <p>Calculate the proportion of cases (rows) that contain a missing value.</p>
-    
-    </div>
-
-    <pre class="usage"><span class='fu'>miss_case_prop</span>(<span class='no'>data</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>a dataframe</p></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>numeric the proportion of cases that contain a missing value</p>
-    
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p><a href='miss_case_pct'>miss_case_pct</a> <code><a href='miss_prop_summary.html'>miss_prop_summary()</a></code> <a href='miss_case_summary'>miss_case_summary</a> <a href='miss_case_table'>miss_case_table</a> <a href='miss_summary'>miss_summary</a> <a href='miss_var_pct'>miss_var_pct</a> <a href='miss_var_prop'>miss_var_prop</a> <a href='miss_var_run'>miss_var_run</a> <a href='miss_var_span'>miss_var_span</a> <a href='miss_var_summary'>miss_var_summary</a> <a href='miss_var_table'>miss_var_table</a></p></div>
-    
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'>
-<span class='fu'>miss_case_prop</span>(<span class='no'>airquality</span>)</div><div class='output co'>#&gt; [1] 0.2745098</div><div class='input'>
-</div></pre>
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diff --git a/docs/reference/miss_case_summary.html b/docs/reference/miss_case_summary.html
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-      <img src="../logo.png" class="logo" alt=""><h1>Summarise the missingness in each case</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/miss-x-summary.R" class="external-link"><code>R/miss-x-summary.R</code></a></small>
-      <div class="d-none name"><code>miss_case_summary.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Provide a summary for each case in the data of the number, percent missings,
-and cumulative sum of missings of the order of the variables. By default,
-it orders by the most missings in each variable.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">miss_case_summary</span><span class="op">(</span><span class="va">data</span>, order <span class="op">=</span> <span class="cn">TRUE</span>, add_cumsum <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>a data.frame</p></dd>
-
-
-<dt>order</dt>
-<dd><p>a logical indicating whether or not to order the result by
-n_miss. Defaults to TRUE. If FALSE, order of cases is the order input.</p></dd>
-
-
-<dt>add_cumsum</dt>
-<dd><p>logical indicating whether or not to add the cumulative
-sum of missings to the data. This can be useful when exploring patterns
-of nonresponse. These are calculated as the cumulative sum of the missings
-in the variables as they are first presented to the function.</p></dd>
-
-
-<dt>...</dt>
-<dd><p>extra arguments</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>a tibble of the percent of missing data in each case.</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="pct-miss-complete-case.html">pct_miss_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_miss_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_miss_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_miss_var()</a></code> <code><a href="pct-miss-complete-case.html">pct_complete_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_complete_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_complete_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_complete_var()</a></code> <code><a href="miss_prop_summary.html">miss_prop_summary()</a></code> <code>miss_case_summary()</code> <code><a href="miss_case_table.html">miss_case_table()</a></code> <code><a href="miss_summary.html">miss_summary()</a></code> <code><a href="miss-pct-prop-defunct.html">miss_var_prop()</a></code> <code><a href="miss_var_run.html">miss_var_run()</a></code> <code><a href="miss_var_span.html">miss_var_span()</a></code> <code><a href="miss_var_summary.html">miss_var_summary()</a></code> <code><a href="miss_var_table.html">miss_var_table()</a></code> <code><a href="n_complete.html">n_complete()</a></code> <code><a href="n_complete_row.html">n_complete_row()</a></code> <code><a href="n_miss.html">n_miss()</a></code> <code><a href="n_miss_row.html">n_miss_row()</a></code> <code><a href="pct_complete.html">pct_complete()</a></code> <code><a href="pct_miss.html">pct_miss()</a></code> <code><a href="prop_complete.html">prop_complete()</a></code> <code><a href="prop_complete_row.html">prop_complete_row()</a></code> <code><a href="prop_miss.html">prop_miss()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">miss_case_summary</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>     case n_miss pct_miss</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>     5      2     33.3</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>    27      2     33.3</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>     6      1     16.7</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>    10      1     16.7</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>    11      1     16.7</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>    25      1     16.7</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>    26      1     16.7</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>    32      1     16.7</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>    33      1     16.7</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>    34      1     16.7</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="co"># works with group_by from dplyr</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">Month</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu">miss_case_summary</span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/miss_case_table.html b/docs/reference/miss_case_table.html
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-      <img src="../logo.png" class="logo" alt=""><h1>Tabulate missings in cases.</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/miss-x-table.R" class="external-link"><code>R/miss-x-table.R</code></a></small>
-      <div class="d-none name"><code>miss_case_table.Rd</code></div>
-    </div>
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-    <div class="ref-description section level2">
-    <p>Provide a tidy table of the number of cases with 0, 1, 2, up to n, missing
-values and the proportion of the number of cases those cases make up.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">miss_case_table</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>a dataframe</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>a dataframe</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="pct-miss-complete-case.html">pct_miss_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_miss_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_miss_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_miss_var()</a></code> <code><a href="pct-miss-complete-case.html">pct_complete_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_complete_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_complete_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_complete_var()</a></code> <code><a href="miss_prop_summary.html">miss_prop_summary()</a></code> <code><a href="miss_case_summary.html">miss_case_summary()</a></code> <code>miss_case_table()</code> <code><a href="miss_summary.html">miss_summary()</a></code> <code><a href="miss-pct-prop-defunct.html">miss_var_prop()</a></code> <code><a href="miss_var_run.html">miss_var_run()</a></code> <code><a href="miss_var_span.html">miss_var_span()</a></code> <code><a href="miss_var_summary.html">miss_var_summary()</a></code> <code><a href="miss_var_table.html">miss_var_table()</a></code> <code><a href="n_complete.html">n_complete()</a></code> <code><a href="n_complete_row.html">n_complete_row()</a></code> <code><a href="n_miss.html">n_miss()</a></code> <code><a href="n_miss_row.html">n_miss_row()</a></code> <code><a href="pct_complete.html">pct_complete()</a></code> <code><a href="pct_miss.html">pct_miss()</a></code> <code><a href="prop_complete.html">prop_complete()</a></code> <code><a href="prop_complete_row.html">prop_complete_row()</a></code> <code><a href="prop_miss.html">prop_miss()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">miss_case_table</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 3 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   n_miss_in_case n_cases pct_cases</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>            <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span>              0     111     72.5 </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span>              1      40     26.1 </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span>              2       2      1.31</span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">Month</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu">miss_case_table</span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/miss_df_pct.html b/docs/reference/miss_df_pct.html
deleted file mode 100644
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-      <div class="row">
-  <div class="col-md-9 contents">
-    <div class="page-header">
-    <h1>Percentage of missing data in a dataframe</h1>
-    </div>
-
-    
-    <p>Calculate the percent of missing data in a dataframe.</p>
-    
-
-    <pre class="usage"><span class='fu'>miss_df_pct</span>(<span class='no'>data</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a> Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>a dataframe</p></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>numeric the percent of missing data in a dataframe</p>
-    
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'>
-<span class='fu'>miss_df_pct</span>(<span class='no'>airquality</span>)</div></pre>
-  </div>
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-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
-      <li><a href="#arguments">Arguments</a></li>
-      
-      <li><a href="#value">Value</a></li>
-      
-      <li><a href="#examples">Examples</a></li>
-    </ul>
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diff --git a/docs/reference/miss_prop_summary.html b/docs/reference/miss_prop_summary.html
deleted file mode 100644
index da7f2b73..00000000
--- a/docs/reference/miss_prop_summary.html
+++ /dev/null
@@ -1,132 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Return missing data info about the dataframe, the variables, and the cases.
-Specifically, returning how many elements in a dataframe contain a missing
-value, how many elements in a variable contain a missing value, and how many
-elements in a case contain a missing."><title>Proportions of missings in data, variables, and cases. — miss_prop_summary • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Proportions of missings in data, variables, and cases. — miss_prop_summary"><meta property="og:description" content="Return missing data info about the dataframe, the variables, and the cases.
-Specifically, returning how many elements in a dataframe contain a missing
-value, how many elements in a variable contain a missing value, and how many
-elements in a case contain a missing."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-      <img src="../logo.png" class="logo" alt=""><h1>Proportions of missings in data, variables, and cases.</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/miss-prop-pct-summary.R" class="external-link"><code>R/miss-prop-pct-summary.R</code></a></small>
-      <div class="d-none name"><code>miss_prop_summary.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Return missing data info about the dataframe, the variables, and the cases.
-Specifically, returning how many elements in a dataframe contain a missing
-value, how many elements in a variable contain a missing value, and how many
-elements in a case contain a missing.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">miss_prop_summary</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>a dataframe</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>a dataframe</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="pct-miss-complete-case.html">pct_miss_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_miss_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_miss_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_miss_var()</a></code> <code><a href="pct-miss-complete-case.html">pct_complete_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_complete_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_complete_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_complete_var()</a></code> <code>miss_prop_summary()</code> <code><a href="miss_case_summary.html">miss_case_summary()</a></code> <code><a href="miss_case_table.html">miss_case_table()</a></code> <code><a href="miss_summary.html">miss_summary()</a></code> <code><a href="miss_var_run.html">miss_var_run()</a></code> <code><a href="miss_var_span.html">miss_var_span()</a></code> <code><a href="miss_var_summary.html">miss_var_summary()</a></code> <code><a href="miss_var_table.html">miss_var_table()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">miss_prop_summary</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 1 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>       df   var  case</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> 0.047<span style="text-decoration: underline;">9</span> 0.333 0.275</span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="co"># respects dplyr::group_by</span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">Month</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu">miss_prop_summary</span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
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diff --git a/docs/reference/miss_scan_count.html b/docs/reference/miss_scan_count.html
deleted file mode 100644
index f0a30c94..00000000
--- a/docs/reference/miss_scan_count.html
+++ /dev/null
@@ -1,167 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Searching for different kinds of missing values is really annoying. If
-you have values like -99 in your data, when they shouldn't be there,
-or they should be encoded as missing, it can be difficult to ascertain
-if they are there, and if so, where they are. miss_scan_count makes it
-easier for users to search for particular occurrences of these values
-across their variables."><title>Search and present different kinds of missing values — miss_scan_count • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Search and present different kinds of missing values — miss_scan_count"><meta property="og:description" content="Searching for different kinds of missing values is really annoying. If
-you have values like -99 in your data, when they shouldn't be there,
-or they should be encoded as missing, it can be difficult to ascertain
-if they are there, and if so, where they are. miss_scan_count makes it
-easier for users to search for particular occurrences of these values
-across their variables."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
-  <a class="external-link nav-link" href="https://github.com/njtierney/naniar/" aria-label="github">
-    <span class="fab fa fab fa-github fa-lg"></span>
-     
-  </a>
-</li>
-      </ul></div>
-
-    
-  </div>
-</nav><div class="container template-reference-topic">
-<div class="row">
-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Search and present different kinds of missing values</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/miss-scan-count.R" class="external-link"><code>R/miss-scan-count.R</code></a></small>
-      <div class="d-none name"><code>miss_scan_count.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Searching for different kinds of missing values is really annoying. If
-you have values like -99 in your data, when they shouldn't be there,
-or they should be encoded as missing, it can be difficult to ascertain
-if they are there, and if so, where they are. <code>miss_scan_count</code> makes it
-easier for users to search for particular occurrences of these values
-across their variables.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">miss_scan_count</span><span class="op">(</span><span class="va">data</span>, <span class="va">search</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>data</p></dd>
-
-
-<dt>search</dt>
-<dd><p>values to search for</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>a dataframe of the occurrences of the values you searched for</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="pct-miss-complete-case.html">pct_miss_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_miss_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_miss_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_miss_var()</a></code> <code><a href="pct-miss-complete-case.html">pct_complete_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_complete_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_complete_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_complete_var()</a></code> <code><a href="miss_prop_summary.html">miss_prop_summary()</a></code> <code><a href="miss_case_summary.html">miss_case_summary()</a></code> <code><a href="miss_case_table.html">miss_case_table()</a></code> <code><a href="miss_summary.html">miss_summary()</a></code> <code><a href="miss-pct-prop-defunct.html">miss_var_prop()</a></code> <code><a href="miss_var_run.html">miss_var_run()</a></code> <code><a href="miss_var_span.html">miss_var_span()</a></code> <code><a href="miss_var_summary.html">miss_var_summary()</a></code> <code><a href="miss_var_table.html">miss_var_table()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">dat_ms</span> <span class="op">&lt;-</span> <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/tribble.html" class="external-link">tribble</a></span><span class="op">(</span><span class="op">~</span><span class="va">x</span>,  <span class="op">~</span><span class="va">y</span>,    <span class="op">~</span><span class="va">z</span>,</span></span>
-<span class="r-in"><span>                         <span class="fl">1</span>,   <span class="st">"A"</span>,   <span class="op">-</span><span class="fl">100</span>,</span></span>
-<span class="r-in"><span>                         <span class="fl">3</span>,   <span class="st">"N/A"</span>, <span class="op">-</span><span class="fl">99</span>,</span></span>
-<span class="r-in"><span>                         <span class="cn">NA</span>,  <span class="cn">NA</span>,    <span class="op">-</span><span class="fl">98</span>,</span></span>
-<span class="r-in"><span>                         <span class="op">-</span><span class="fl">99</span>, <span class="st">"E"</span>,   <span class="op">-</span><span class="fl">101</span>,</span></span>
-<span class="r-in"><span>                         <span class="op">-</span><span class="fl">98</span>, <span class="st">"F"</span>,   <span class="op">-</span><span class="fl">1</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">miss_scan_count</span><span class="op">(</span><span class="va">dat_ms</span>,<span class="op">-</span><span class="fl">99</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 3 × 2</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   Variable     n</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> x            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> y            0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> z            1</span>
-<span class="r-in"><span><span class="fu">miss_scan_count</span><span class="op">(</span><span class="va">dat_ms</span>,<span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="op">-</span><span class="fl">99</span>,<span class="op">-</span><span class="fl">98</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 3 × 2</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   Variable     n</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> x            2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> y            0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> z            2</span>
-<span class="r-in"><span><span class="fu">miss_scan_count</span><span class="op">(</span><span class="va">dat_ms</span>,<span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"-99"</span>,<span class="st">"-98"</span>,<span class="st">"N/A"</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 3 × 2</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   Variable     n</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> x            2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> y            1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> z            2</span>
-<span class="r-in"><span><span class="fu">miss_scan_count</span><span class="op">(</span><span class="va">dat_ms</span>,<span class="va">common_na_strings</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 3 × 2</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   Variable     n</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> x            4</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> y            4</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> z            5</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
-
-
-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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diff --git a/docs/reference/miss_summary.html b/docs/reference/miss_summary.html
deleted file mode 100644
index d6b4504c..00000000
--- a/docs/reference/miss_summary.html
+++ /dev/null
@@ -1,153 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="miss_summary performs all of the missing data helper summaries and puts
-them into lists within a tibble"><title>Collate summary measures from naniar into one tibble — miss_summary • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Collate summary measures from naniar into one tibble — miss_summary"><meta property="og:description" content="miss_summary performs all of the missing data helper summaries and puts
-them into lists within a tibble"><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-
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-    <a class="dropdown-item" href="../articles/replace-with-na.html">Replace with NA</a>
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-<div class="row">
-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Collate summary measures from naniar into one tibble</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/miss-x-summary.R" class="external-link"><code>R/miss-x-summary.R</code></a></small>
-      <div class="d-none name"><code>miss_summary.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p><code>miss_summary</code> performs all of the missing data helper summaries and puts
-them into lists within a tibble</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">miss_summary</span><span class="op">(</span><span class="va">data</span>, order <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>a dataframe</p></dd>
-
-
-<dt>order</dt>
-<dd><p>whether or not to order the result by n_miss</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>a tibble of missing data summaries</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="pct-miss-complete-case.html">pct_miss_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_miss_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_miss_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_miss_var()</a></code> <code><a href="pct-miss-complete-case.html">pct_complete_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_complete_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_complete_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_complete_var()</a></code> <code><a href="miss_prop_summary.html">miss_prop_summary()</a></code> <code><a href="miss_case_summary.html">miss_case_summary()</a></code> <code><a href="miss_case_table.html">miss_case_table()</a></code> <code>miss_summary()</code> <code><a href="miss-pct-prop-defunct.html">miss_var_prop()</a></code> <code><a href="miss_var_run.html">miss_var_run()</a></code> <code><a href="miss_var_span.html">miss_var_span()</a></code> <code><a href="miss_var_summary.html">miss_var_summary()</a></code> <code><a href="miss_var_table.html">miss_var_table()</a></code> <code><a href="n_complete.html">n_complete()</a></code> <code><a href="n_complete_row.html">n_complete_row()</a></code> <code><a href="n_miss.html">n_miss()</a></code> <code><a href="n_miss_row.html">n_miss_row()</a></code> <code><a href="pct_complete.html">pct_complete()</a></code> <code><a href="pct_miss.html">pct_miss()</a></code> <code><a href="prop_complete.html">prop_complete()</a></code> <code><a href="prop_complete_row.html">prop_complete_row()</a></code> <code><a href="prop_miss.html">prop_miss()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">s_miss</span> <span class="op">&lt;-</span> <span class="fu">miss_summary</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="va">s_miss</span><span class="op">$</span><span class="va">miss_df_prop</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.04793028</span>
-<span class="r-in"><span><span class="va">s_miss</span><span class="op">$</span><span class="va">miss_case_table</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [[1]]</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 3 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   n_miss_in_case n_cases pct_cases</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>            <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span>              0     111     72.5 </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span>              1      40     26.1 </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span>              2       2      1.31</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
-<span class="r-in"><span><span class="va">s_miss</span><span class="op">$</span><span class="va">miss_var_summary</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [[1]]</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 6 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   variable n_miss pct_miss</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> Ozone        37    24.2 </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> Solar.R       7     4.58</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> Wind          0     0   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span> Temp          0     0   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span> Month         0     0   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">6</span> Day           0     0   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
-<span class="r-in"><span><span class="co"># etc, etc, etc.</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="va">s_miss_group</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">airquality</span>, <span class="va">Month</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu">miss_summary</span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="va">s_miss_group</span><span class="op">$</span><span class="va">miss_df_prop</span></span></span>
-<span class="r-in"><span><span class="va">s_miss_group</span><span class="op">$</span><span class="va">miss_case_table</span></span></span>
-<span class="r-in"><span><span class="co"># etc, etc, etc.</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/miss_var_cumsum.html b/docs/reference/miss_var_cumsum.html
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-      <img src="../logo.png" class="logo" alt=""><h1>Cumulative sum of the number of missings in each variable</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/miss-x-cumsum.R" class="external-link"><code>R/miss-x-cumsum.R</code></a></small>
-      <div class="d-none name"><code>miss_var_cumsum.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Calculate the cumulative sum of number &amp; percentage of
-missingness for each variable.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">miss_var_cumsum</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>a data.frame</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>a tibble of the cumulative sum of missing data in each variable</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="pct-miss-complete-case.html">pct_miss_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_miss_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_miss_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_miss_var()</a></code> <code><a href="pct-miss-complete-case.html">pct_complete_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_complete_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_complete_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_complete_var()</a></code> <code><a href="miss_prop_summary.html">miss_prop_summary()</a></code> <code><a href="miss_case_summary.html">miss_case_summary()</a></code> <code><a href="miss_case_table.html">miss_case_table()</a></code> <code><a href="miss_summary.html">miss_summary()</a></code> <code><a href="miss-pct-prop-defunct.html">miss_var_prop()</a></code> <code><a href="miss_var_run.html">miss_var_run()</a></code> <code><a href="miss_var_span.html">miss_var_span()</a></code> <code><a href="miss_var_summary.html">miss_var_summary()</a></code> <code><a href="miss_var_table.html">miss_var_table()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">miss_var_cumsum</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 6 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   variable n_miss n_miss_cumsum</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> Ozone        37            37</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> Solar.R       7            44</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> Wind          0            44</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span> Temp          0            44</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span> Month         0            44</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">6</span> Day           0            44</span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># respects dplyr::group_by</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">Month</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu">miss_var_cumsum</span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/miss_var_pct.html b/docs/reference/miss_var_pct.html
deleted file mode 100644
index 094d3973..00000000
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-    <h1>Percentage of variables containing missings</h1>
-    <small class="dont-index">Source: <a href='https://github.com/njtierney/naniar/blob/master/R/miss-x-pct-prop.R'><code>R/miss-x-pct-prop.R</code></a></small>
-    <div class="hidden name"><code>miss_var_pct.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    
-    <p>Calculate the percentage of variables that contain a single missing value.</p>
-    
-    </div>
-
-    <pre class="usage"><span class='fu'>miss_var_pct</span>(<span class='no'>data</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>a dataframe</p></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>numeric the percent of variables that contain missing data</p>
-    
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p><a href='miss_case_pct'>miss_case_pct</a> <a href='miss_case_prop'>miss_case_prop</a> <code><a href='miss_prop_summary.html'>miss_prop_summary()</a></code> <a href='miss_case_summary'>miss_case_summary</a> <a href='miss_case_table'>miss_case_table</a> <a href='miss_summary'>miss_summary</a> <a href='miss_var_prop'>miss_var_prop</a> <a href='miss_var_run'>miss_var_run</a> <a href='miss_var_span'>miss_var_span</a> <a href='miss_var_summary'>miss_var_summary</a> <a href='miss_var_table'>miss_var_table</a></p></div>
-    
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'>
-<span class='fu'>miss_var_pct</span>(<span class='no'>riskfactors</span>)</div><div class='output co'>#&gt; [1] 70.58824</div><div class='input'><span class='fu'>miss_var_pct</span>(<span class='no'>oceanbuoys</span>)</div><div class='output co'>#&gt; [1] 37.5</div><div class='input'>
-</div></pre>
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-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
-      <li><a href="#arguments">Arguments</a></li>
-      
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-
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diff --git a/docs/reference/miss_var_prop.html b/docs/reference/miss_var_prop.html
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-    <h1>Proportion of variables containing missings</h1>
-    <small class="dont-index">Source: <a href='https://github.com/njtierney/naniar/blob/master/R/miss-x-pct-prop.R'><code>R/miss-x-pct-prop.R</code></a></small>
-    <div class="hidden name"><code>miss_var_prop.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    
-    <p>Calculate the proportion of variables that contain a single missing value.</p>
-    
-    </div>
-
-    <pre class="usage"><span class='fu'>miss_var_prop</span>(<span class='no'>data</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>a dataframe</p></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>numeric the proportion of variables that contain missing data</p>
-    
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p><a href='miss_case_pct'>miss_case_pct</a> <a href='miss_case_prop'>miss_case_prop</a> <code><a href='miss_prop_summary.html'>miss_prop_summary()</a></code> <a href='miss_case_summary'>miss_case_summary</a> <a href='miss_case_table'>miss_case_table</a> <a href='miss_summary'>miss_summary</a> <a href='miss_var_pct'>miss_var_pct</a> <a href='miss_var_run'>miss_var_run</a> <a href='miss_var_span'>miss_var_span</a> <a href='miss_var_summary'>miss_var_summary</a> <a href='miss_var_table'>miss_var_table</a></p></div>
-    
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'>
-<span class='fu'>miss_var_prop</span>(<span class='no'>riskfactors</span>)</div><div class='output co'>#&gt; [1] 0.7058824</div><div class='input'><span class='fu'>miss_var_prop</span>(<span class='no'>oceanbuoys</span>)</div><div class='output co'>#&gt; [1] 0.375</div><div class='input'>
-</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
-      <li><a href="#arguments">Arguments</a></li>
-      
-      <li><a href="#value">Value</a></li>
-
-      <li><a href="#see-also">See also</a></li>
-      
-      <li><a href="#examples">Examples</a></li>
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diff --git a/docs/reference/miss_var_run.html b/docs/reference/miss_var_run.html
deleted file mode 100644
index c6edb793..00000000
--- a/docs/reference/miss_var_run.html
+++ /dev/null
@@ -1,173 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content='It us useful to find the number of missing values that occur in a single run.
-The function, miss_var_run(), returns a dataframe with the column names
-"run_length" and "is_na", which describe the length of the run, and
-whether that run describes a missing value.'><title>Find the number of missing and complete values in a single run — miss_var_run • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Find the number of missing and complete values in a single run — miss_var_run"><meta property="og:description" content='It us useful to find the number of missing values that occur in a single run.
-The function, miss_var_run(), returns a dataframe with the column names
-"run_length" and "is_na", which describe the length of the run, and
-whether that run describes a missing value.'><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Find the number of missing and complete values in a single run</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/miss-x-run.R" class="external-link"><code>R/miss-x-run.R</code></a></small>
-      <div class="d-none name"><code>miss_var_run.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>It us useful to find the number of missing values that occur in a single run.
-The function, <code>miss_var_run()</code>, returns a dataframe with the column names
-"run_length" and "is_na", which describe the length of the run, and
-whether that run describes a missing value.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">miss_var_run</span><span class="op">(</span><span class="va">data</span>, <span class="va">var</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>data.frame</p></dd>
-
-
-<dt>var</dt>
-<dd><p>a bare variable name</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>dataframe with column names "run_length" and "is_na", which describe
-the length of the run, and whether that run describes a missing value.</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="pct-miss-complete-case.html">pct_miss_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_miss_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_miss_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_miss_var()</a></code> <code><a href="pct-miss-complete-case.html">pct_complete_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_complete_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_complete_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_complete_var()</a></code> <code><a href="miss_prop_summary.html">miss_prop_summary()</a></code> <code><a href="miss_case_summary.html">miss_case_summary()</a></code> <code><a href="miss_case_table.html">miss_case_table()</a></code> <code><a href="miss_summary.html">miss_summary()</a></code> <code><a href="miss-pct-prop-defunct.html">miss_var_prop()</a></code> <code>miss_var_run()</code> <code><a href="miss_var_span.html">miss_var_span()</a></code> <code><a href="miss_var_summary.html">miss_var_summary()</a></code> <code><a href="miss_var_table.html">miss_var_table()</a></code> <code><a href="n_complete.html">n_complete()</a></code> <code><a href="n_complete_row.html">n_complete_row()</a></code> <code><a href="n_miss.html">n_miss()</a></code> <code><a href="n_miss_row.html">n_miss_row()</a></code> <code><a href="pct_complete.html">pct_complete()</a></code> <code><a href="pct_miss.html">pct_miss()</a></code> <code><a href="prop_complete.html">prop_complete()</a></code> <code><a href="prop_complete_row.html">prop_complete_row()</a></code> <code><a href="prop_miss.html">prop_miss()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">miss_var_run</span><span class="op">(</span><span class="va">pedestrian</span>, <span class="va">hourly_counts</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 35 × 2</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    run_length is_na   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>       <span style="text-decoration: underline;">6</span>628 complete</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>          1 missing </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>       <span style="text-decoration: underline;">5</span>250 complete</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>        624 missing </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>       <span style="text-decoration: underline;">3</span>652 complete</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>          1 missing </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>       <span style="text-decoration: underline;">1</span>290 complete</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>        744 missing </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>       <span style="text-decoration: underline;">7</span>420 complete</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>          1 missing </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 25 more rows</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="co"># find the number of runs missing/complete for each month</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">pedestrian</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">month</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu">miss_var_run</span><span class="op">(</span><span class="va">hourly_counts</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># explore the number of missings in a given run</span></span></span>
-<span class="r-in"><span><span class="fu">miss_var_run</span><span class="op">(</span><span class="va">pedestrian</span>, <span class="va">hourly_counts</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">is_na</span> <span class="op">==</span> <span class="st">"missing"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/count.html" class="external-link">count</a></span><span class="op">(</span><span class="va">run_length</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">run_length</span>,</span></span>
-<span class="r-in"><span>             y <span class="op">=</span> <span class="va">n</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span></span>
-<span class="r-in"><span>      <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_bar.html" class="external-link">geom_col</a></span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># look at the number of missing values and the run length of these.</span></span></span>
-<span class="r-in"><span><span class="fu">miss_var_run</span><span class="op">(</span><span class="va">pedestrian</span>, <span class="va">hourly_counts</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">is_na</span>,</span></span>
-<span class="r-in"><span>             y <span class="op">=</span> <span class="va">run_length</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span></span>
-<span class="r-in"><span>      <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_boxplot.html" class="external-link">geom_boxplot</a></span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># using group_by</span></span></span>
-<span class="r-in"><span> <span class="va">pedestrian</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>   <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">month</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>   <span class="fu">miss_var_run</span><span class="op">(</span><span class="va">hourly_counts</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
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diff --git a/docs/reference/miss_var_span.html b/docs/reference/miss_var_span.html
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+++ /dev/null
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-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="To summarise the missing values in a time series object it can be useful to
-calculate the number of missing values in a given time period.
-miss_var_span takes a data.frame object, a variable, and a span_every
-argument and returns a dataframe containing the number of missing values
-within each span. When the number of observations isn't a perfect
-multiple of the span length, the final span is whatever the last
-remainder is. For example, the pedestrian dataset has 37,700 rows. If
-the span is set to 4000, then there will be 1700 rows remaining. This can
-be provided using modulo (%%): nrow(data) %% 4000. This remainder
-number is provided in n_in_span."><title>Summarise the number of missings for a given repeating span on a variable — miss_var_span • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Summarise the number of missings for a given repeating span on a variable — miss_var_span"><meta property="og:description" content="To summarise the missing values in a time series object it can be useful to
-calculate the number of missing values in a given time period.
-miss_var_span takes a data.frame object, a variable, and a span_every
-argument and returns a dataframe containing the number of missing values
-within each span. When the number of observations isn't a perfect
-multiple of the span length, the final span is whatever the last
-remainder is. For example, the pedestrian dataset has 37,700 rows. If
-the span is set to 4000, then there will be 1700 rows remaining. This can
-be provided using modulo (%%): nrow(data) %% 4000. This remainder
-number is provided in n_in_span."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-<div class="row">
-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Summarise the number of missings for a given repeating span on a variable</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/miss-x-span.R" class="external-link"><code>R/miss-x-span.R</code></a></small>
-      <div class="d-none name"><code>miss_var_span.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>To summarise the missing values in a time series object it can be useful to
-calculate the number of missing values in a given time period.
-<code>miss_var_span</code> takes a data.frame object, a variable, and a <code>span_every</code>
-argument and returns a dataframe containing the number of missing values
-within each span. When the number of observations isn't a perfect
-multiple of the span length, the final span is whatever the last
-remainder is. For example, the <code>pedestrian</code> dataset has 37,700 rows. If
-the span is set to 4000, then there will be 1700 rows remaining. This can
-be provided using modulo (<code>%%</code>): <code>nrow(data) %% 4000</code>. This remainder
-number is provided in <code>n_in_span</code>.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">miss_var_span</span><span class="op">(</span><span class="va">data</span>, <span class="va">var</span>, <span class="va">span_every</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>data.frame</p></dd>
-
-
-<dt>var</dt>
-<dd><p>bare unquoted variable name of interest.</p></dd>
-
-
-<dt>span_every</dt>
-<dd><p>integer describing the length of the span to be explored</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>dataframe with variables <code>n_miss</code>, <code>n_complete</code>, <code>prop_miss</code>, and
-<code>prop_complete</code>, which describe the number, or proportion of missing or
-complete values within that given time span. The final variable,
-<code>n_in_span</code> states how many observations are in the span.</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="pct-miss-complete-case.html">pct_miss_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_miss_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_miss_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_miss_var()</a></code> <code><a href="pct-miss-complete-case.html">pct_complete_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_complete_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_complete_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_complete_var()</a></code> <code><a href="miss_prop_summary.html">miss_prop_summary()</a></code> <code><a href="miss_case_summary.html">miss_case_summary()</a></code> <code><a href="miss_case_table.html">miss_case_table()</a></code> <code><a href="miss_summary.html">miss_summary()</a></code> <code><a href="miss-pct-prop-defunct.html">miss_var_prop()</a></code> <code><a href="miss_var_run.html">miss_var_run()</a></code> <code>miss_var_span()</code> <code><a href="miss_var_summary.html">miss_var_summary()</a></code> <code><a href="miss_var_table.html">miss_var_table()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">miss_var_span</span><span class="op">(</span>data <span class="op">=</span> <span class="va">pedestrian</span>,</span></span>
-<span class="r-in"><span>             var <span class="op">=</span> <span class="va">hourly_counts</span>,</span></span>
-<span class="r-in"><span>             span_every <span class="op">=</span> <span class="fl">168</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 225 × 6</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    span_counter n_miss n_complete prop_miss prop_complete n_in_span</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>           <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>            1      0        168         0             1       168</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>            2      0        168         0             1       168</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>            3      0        168         0             1       168</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>            4      0        168         0             1       168</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>            5      0        168         0             1       168</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>            6      0        168         0             1       168</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>            7      0        168         0             1       168</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>            8      0        168         0             1       168</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>            9      0        168         0             1       168</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>           10      0        168         0             1       168</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 215 more rows</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span> <span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span> <span class="va">pedestrian</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>   <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">month</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>     <span class="fu">miss_var_span</span><span class="op">(</span>var <span class="op">=</span> <span class="va">hourly_counts</span>,</span></span>
-<span class="r-in"><span>                   span_every <span class="op">=</span> <span class="fl">168</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/miss_var_summary.html b/docs/reference/miss_var_summary.html
deleted file mode 100644
index 65c949ff..00000000
--- a/docs/reference/miss_var_summary.html
+++ /dev/null
@@ -1,170 +0,0 @@
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-cumulative sum of missings of the order of the variables. By default,
-it orders by the most missings in each variable."><title>Summarise the missingness in each variable — miss_var_summary • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Summarise the missingness in each variable — miss_var_summary"><meta property="og:description" content="Provide a summary for each variable of the number, percent missings, and
-cumulative sum of missings of the order of the variables. By default,
-it orders by the most missings in each variable."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Summarise the missingness in each variable</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/miss-x-summary.R" class="external-link"><code>R/miss-x-summary.R</code></a></small>
-      <div class="d-none name"><code>miss_var_summary.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Provide a summary for each variable of the number, percent missings, and
-cumulative sum of missings of the order of the variables. By default,
-it orders by the most missings in each variable.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">miss_var_summary</span><span class="op">(</span><span class="va">data</span>, order <span class="op">=</span> <span class="cn">FALSE</span>, add_cumsum <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>a data.frame</p></dd>
-
-
-<dt>order</dt>
-<dd><p>a logical indicating whether to order the result by <code>n_miss</code>.
-Defaults to TRUE. If FALSE, order of variables is the order input.</p></dd>
-
-
-<dt>add_cumsum</dt>
-<dd><p>logical indicating whether or not to add the cumulative
-sum of missings to the data. This can be useful when exploring patterns
-of nonresponse. These are calculated as the cumulative sum of the missings
-in the variables as they are first presented to the function.</p></dd>
-
-
-<dt>...</dt>
-<dd><p>extra arguments</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>a tibble of the percent of missing data in each variable</p>
-    </div>
-    <div class="section level2">
-    <h2 id="note">Note<a class="anchor" aria-label="anchor" href="#note"></a></h2>
-    <p><code>n_miss_cumsum</code> is calculated as the cumulative sum of missings in the
-variables in the order that they are given in the data when entering
-the function</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="pct-miss-complete-case.html">pct_miss_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_miss_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_miss_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_miss_var()</a></code> <code><a href="pct-miss-complete-case.html">pct_complete_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_complete_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_complete_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_complete_var()</a></code> <code><a href="miss_prop_summary.html">miss_prop_summary()</a></code> <code><a href="miss_case_summary.html">miss_case_summary()</a></code> <code><a href="miss_case_table.html">miss_case_table()</a></code> <code><a href="miss_summary.html">miss_summary()</a></code> <code><a href="miss-pct-prop-defunct.html">miss_var_prop()</a></code> <code><a href="miss_var_run.html">miss_var_run()</a></code> <code><a href="miss_var_span.html">miss_var_span()</a></code> <code>miss_var_summary()</code> <code><a href="miss_var_table.html">miss_var_table()</a></code> <code><a href="n_complete.html">n_complete()</a></code> <code><a href="n_complete_row.html">n_complete_row()</a></code> <code><a href="n_miss.html">n_miss()</a></code> <code><a href="n_miss_row.html">n_miss_row()</a></code> <code><a href="pct_complete.html">pct_complete()</a></code> <code><a href="pct_miss.html">pct_miss()</a></code> <code><a href="prop_complete.html">prop_complete()</a></code> <code><a href="prop_complete_row.html">prop_complete_row()</a></code> <code><a href="prop_miss.html">prop_miss()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">miss_var_summary</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 6 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   variable n_miss pct_miss</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> Ozone        37    24.2 </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> Solar.R       7     4.58</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> Wind          0     0   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span> Temp          0     0   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span> Month         0     0   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">6</span> Day           0     0   </span>
-<span class="r-in"><span><span class="fu">miss_var_summary</span><span class="op">(</span><span class="va">oceanbuoys</span>, order <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 8 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   variable   n_miss pct_miss</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>       <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> humidity       93   12.6  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> air_temp_c     81   11.0  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> sea_temp_c      3    0.408</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span> year            0    0    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span> latitude        0    0    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">6</span> longitude       0    0    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">7</span> wind_ew         0    0    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">8</span> wind_ns         0    0    </span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="co"># works with group_by from dplyr</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">Month</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu">miss_var_summary</span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
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diff --git a/docs/reference/miss_var_table.html b/docs/reference/miss_var_table.html
deleted file mode 100644
index eb52b4e8..00000000
--- a/docs/reference/miss_var_table.html
+++ /dev/null
@@ -1,131 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Provide a tidy table of the number of variables with 0, 1, 2, up to n,
-missing values and the proportion of the number of variables those
-variables make up."><title>Tabulate the missings in the variables — miss_var_table • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Tabulate the missings in the variables — miss_var_table"><meta property="og:description" content="Provide a tidy table of the number of variables with 0, 1, 2, up to n,
-missing values and the proportion of the number of variables those
-variables make up."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
-<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
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-      <img src="../logo.png" class="logo" alt=""><h1>Tabulate the missings in the variables</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/miss-x-table.R" class="external-link"><code>R/miss-x-table.R</code></a></small>
-      <div class="d-none name"><code>miss_var_table.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Provide a tidy table of the number of variables with 0, 1, 2, up to n,
-missing values and the proportion of the number of variables those
-variables make up.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">miss_var_table</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>a dataframe</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>a dataframe</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="pct-miss-complete-case.html">pct_miss_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_miss_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_miss_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_miss_var()</a></code> <code><a href="pct-miss-complete-case.html">pct_complete_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_complete_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_complete_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_complete_var()</a></code> <code><a href="miss_prop_summary.html">miss_prop_summary()</a></code> <code><a href="miss_case_summary.html">miss_case_summary()</a></code> <code><a href="miss_case_table.html">miss_case_table()</a></code> <code><a href="miss_summary.html">miss_summary()</a></code> <code><a href="miss-pct-prop-defunct.html">miss_var_prop()</a></code> <code><a href="miss_var_run.html">miss_var_run()</a></code> <code><a href="miss_var_span.html">miss_var_span()</a></code> <code><a href="miss_var_summary.html">miss_var_summary()</a></code> <code>miss_var_table()</code> <code><a href="n_complete.html">n_complete()</a></code> <code><a href="n_complete_row.html">n_complete_row()</a></code> <code><a href="n_miss.html">n_miss()</a></code> <code><a href="n_miss_row.html">n_miss_row()</a></code> <code><a href="pct_complete.html">pct_complete()</a></code> <code><a href="pct_miss.html">pct_miss()</a></code> <code><a href="prop_complete.html">prop_complete()</a></code> <code><a href="prop_complete_row.html">prop_complete_row()</a></code> <code><a href="prop_miss.html">prop_miss()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">miss_var_table</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 3 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   n_miss_in_var n_vars pct_vars</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>           <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span>             0      4     66.7</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span>             7      1     16.7</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span>            37      1     16.7</span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">Month</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu">miss_var_table</span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
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-    <footer><div class="pkgdown-footer-left">
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diff --git a/docs/reference/miss_var_which.html b/docs/reference/miss_var_which.html
deleted file mode 100644
index a0e3645d..00000000
--- a/docs/reference/miss_var_which.html
+++ /dev/null
@@ -1,122 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="It can be helpful when writing other functions to just return the names
-of the variables that contain missing values. miss_var_which returns a
-vector of variable names that contain missings. It will return NULL when
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-of the variables that contain missing values. miss_var_which returns a
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-      <img src="../logo.png" class="logo" alt=""><h1>Which variables contain missing values?</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/where-na.R" class="external-link"><code>R/where-na.R</code></a></small>
-      <div class="d-none name"><code>miss_var_which.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>It can be helpful when writing other functions to just return the names
-of the variables that contain missing values. <code>miss_var_which</code> returns a
-vector of variable names that contain missings. It will return NULL when
-there are no missings.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">miss_var_which</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>a data.frame</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>character vector of variable names</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="fu">miss_var_which</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] "Ozone"   "Solar.R"</span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">miss_var_which</span><span class="op">(</span><span class="va">mtcars</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> NULL</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/n-var-case-complete.html b/docs/reference/n-var-case-complete.html
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+++ /dev/null
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-<!DOCTYPE html>
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-      <img src="../logo.png" class="logo" alt=""><h1>The number of variables with complete values</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/n-var-miss.R" class="external-link"><code>R/n-var-miss.R</code></a></small>
-      <div class="d-none name"><code>n-var-case-complete.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>This function calculates the number of variables that contain a complete value</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">n_var_complete</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">n_case_complete</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>data.frame</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>integer number of complete values</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="n-var-case-miss.html">n_var_miss()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># how many variables contain complete values?</span></span></span>
-<span class="r-in"><span><span class="fu">n_var_complete</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 4</span>
-<span class="r-in"><span><span class="fu">n_case_complete</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 111</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
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-    </nav></aside></div>
-
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-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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diff --git a/docs/reference/n-var-case-miss.html b/docs/reference/n-var-case-miss.html
deleted file mode 100644
index 57dba0fb..00000000
--- a/docs/reference/n-var-case-miss.html
+++ /dev/null
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-      <img src="../logo.png" class="logo" alt=""><h1>The number of variables or cases with missing values</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/n-var-miss.R" class="external-link"><code>R/n-var-miss.R</code></a></small>
-      <div class="d-none name"><code>n-var-case-miss.Rd</code></div>
-    </div>
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-    <div class="ref-description section level2">
-    <p>This function calculates the number of variables or cases that contain a missing value</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">n_var_miss</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">n_case_miss</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>data.frame</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>integer, number of missings</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="n-var-case-complete.html">n_var_complete()</a></code></p></div>
-    </div>
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-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># how many variables contain missing values?</span></span></span>
-<span class="r-in"><span><span class="fu">n_var_miss</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 2</span>
-<span class="r-in"><span><span class="fu">n_case_miss</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 42</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/n_complete.html b/docs/reference/n_complete.html
deleted file mode 100644
index e15f4e8c..00000000
--- a/docs/reference/n_complete.html
+++ /dev/null
@@ -1,113 +0,0 @@
-<!DOCTYPE html>
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-      <img src="../logo.png" class="logo" alt=""><h1>Return the number of complete values</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/n-prop-miss-complete.R" class="external-link"><code>R/n-prop-miss-complete.R</code></a></small>
-      <div class="d-none name"><code>n_complete.Rd</code></div>
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-    <p>A complement to <code>n_miss</code></p>
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-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">n_complete</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
-<dd><p>a vector</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>numeric number of complete values</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">n_complete</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 874</span>
-<span class="r-in"><span><span class="fu">n_complete</span><span class="op">(</span><span class="va">airquality</span><span class="op">$</span><span class="va">Ozone</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 116</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/n_complete_row.html b/docs/reference/n_complete_row.html
deleted file mode 100644
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--- a/docs/reference/n_complete_row.html
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-is a dataframe</p>
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-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">n_complete_row</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></code></pre></div>
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-    <dl><dt>data</dt>
-<dd><p>a dataframe</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>numeric vector of the number of complete values in each row</p>
-    </div>
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-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="pct-miss-complete-case.html">pct_miss_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_miss_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_miss_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_miss_var()</a></code> <code><a href="pct-miss-complete-case.html">pct_complete_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_complete_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_complete_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_complete_var()</a></code> <code><a href="miss_prop_summary.html">miss_prop_summary()</a></code> <code><a href="miss_case_summary.html">miss_case_summary()</a></code> <code><a href="miss_case_table.html">miss_case_table()</a></code> <code><a href="miss_summary.html">miss_summary()</a></code> <code><a href="miss-pct-prop-defunct.html">miss_var_prop()</a></code> <code><a href="miss_var_run.html">miss_var_run()</a></code> <code><a href="miss_var_span.html">miss_var_span()</a></code> <code><a href="miss_var_summary.html">miss_var_summary()</a></code> <code><a href="miss_var_table.html">miss_var_table()</a></code> <code><a href="n_complete.html">n_complete()</a></code> <code>n_complete_row()</code> <code><a href="n_miss.html">n_miss()</a></code> <code><a href="n_miss_row.html">n_miss_row()</a></code> <code><a href="pct_complete.html">pct_complete()</a></code> <code><a href="pct_miss.html">pct_miss()</a></code> <code><a href="prop_complete.html">prop_complete()</a></code> <code><a href="prop_complete_row.html">prop_complete_row()</a></code> <code><a href="prop_miss.html">prop_miss()</a></code></p></div>
-    </div>
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-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">n_complete_row</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   [1] 6 6 6 6 4 5 6 6 6 5 5 6 6 6 6 6 6 6 6 6 6 6 6 6 5 5 4 6 6 6 6 5 5 5 5 5 5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [38] 6 5 6 6 5 5 6 5 5 6 6 6 6 6 5 5 5 5 5 5 5 5 5 5 6 6 6 5 6 6 6 6 6 6 5 6 6</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [75] 5 6 6 6 6 6 6 6 5 5 6 6 6 6 6 6 6 6 6 6 6 5 5 5 6 6 6 5 5 6 6 6 5 6 6 6 6</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [112] 6 6 6 5 6 6 6 5 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [149] 6 5 6 6 6</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/n_miss.html b/docs/reference/n_miss.html
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-      <img src="../logo.png" class="logo" alt=""><h1>Return the number of missing values</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/n-prop-miss-complete.R" class="external-link"><code>R/n-prop-miss-complete.R</code></a></small>
-      <div class="d-none name"><code>n_miss.Rd</code></div>
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-    <div class="ref-description section level2">
-    <p>Substitute for <code>sum(is.na(data))</code></p>
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-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">n_miss</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span></code></pre></div>
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-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
-<dd><p>a vector</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
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-<p>numeric the number of missing values</p>
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-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">n_miss</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 44</span>
-<span class="r-in"><span><span class="fu">n_miss</span><span class="op">(</span><span class="va">airquality</span><span class="op">$</span><span class="va">Ozone</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 37</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/n_miss_row.html b/docs/reference/n_miss_row.html
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+++ /dev/null
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-<!DOCTYPE html>
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-is a dataframe"><title>Return a vector of the number of missing values in each row — n_miss_row • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Return a vector of the number of missing values in each row — n_miss_row"><meta property="og:description" content="Substitute for rowSums(is.na(data)), but it also checks if input is NULL or
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-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/n-prop-miss-complete-rows.R" class="external-link"><code>R/n-prop-miss-complete-rows.R</code></a></small>
-      <div class="d-none name"><code>n_miss_row.Rd</code></div>
-    </div>
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-    <div class="ref-description section level2">
-    <p>Substitute for <code>rowSums(is.na(data))</code>, but it also checks if input is NULL or
-is a dataframe</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">n_miss_row</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>a dataframe</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>numeric vector of the number of missing values in each row</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="pct-miss-complete-case.html">pct_miss_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_miss_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_miss_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_miss_var()</a></code> <code><a href="pct-miss-complete-case.html">pct_complete_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_complete_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_complete_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_complete_var()</a></code> <code><a href="miss_prop_summary.html">miss_prop_summary()</a></code> <code><a href="miss_case_summary.html">miss_case_summary()</a></code> <code><a href="miss_case_table.html">miss_case_table()</a></code> <code><a href="miss_summary.html">miss_summary()</a></code> <code><a href="miss-pct-prop-defunct.html">miss_var_prop()</a></code> <code><a href="miss_var_run.html">miss_var_run()</a></code> <code><a href="miss_var_span.html">miss_var_span()</a></code> <code><a href="miss_var_summary.html">miss_var_summary()</a></code> <code><a href="miss_var_table.html">miss_var_table()</a></code> <code><a href="n_complete.html">n_complete()</a></code> <code><a href="n_complete_row.html">n_complete_row()</a></code> <code><a href="n_miss.html">n_miss()</a></code> <code>n_miss_row()</code> <code><a href="pct_complete.html">pct_complete()</a></code> <code><a href="pct_miss.html">pct_miss()</a></code> <code><a href="prop_complete.html">prop_complete()</a></code> <code><a href="prop_complete_row.html">prop_complete_row()</a></code> <code><a href="prop_miss.html">prop_miss()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">n_miss_row</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   [1] 0 0 0 0 2 1 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 2 0 0 0 0 1 1 1 1 1 1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [38] 0 1 0 0 1 1 0 1 1 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 0 0 0 1 0 0 0 0 0 0 1 0 0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [75] 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 1 1 0 0 0 1 0 0 0 0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [112] 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [149] 0 1 0 0 0</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/nabular.html b/docs/reference/nabular.html
deleted file mode 100644
index 2acd3c94..00000000
--- a/docs/reference/nabular.html
+++ /dev/null
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-<!DOCTYPE html>
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-      <img src="../logo.png" class="logo" alt=""><h1>Convert data into nabular form by binding shade to it</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/nabular.R" class="external-link"><code>R/nabular.R</code></a></small>
-      <div class="d-none name"><code>nabular.Rd</code></div>
-    </div>
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-    <p>Binding a shadow matrix to a regular dataframe converts it into nabular data,
-which makes it easier to visualise and work with missing data.</p>
-    </div>
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-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">nabular</span><span class="op">(</span><span class="va">data</span>, only_miss <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
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-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>a dataframe</p></dd>
-
-
-<dt>only_miss</dt>
-<dd><p>logical - if FALSE (default) it will bind a dataframe with
-all of the variables duplicated with their shadow. Setting this to TRUE
-will bind variables only those variables that contain missing values.
-See the examples for more details.</p></dd>
-
-
-<dt>...</dt>
-<dd><p>extra options to pass to <code><a href="recode_shadow.html">recode_shadow()</a></code> - a work in progress.</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>data with the added variable shifted and the suffix <code>_NA</code></p>
-
-
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="bind_shadow.html">bind_shadow()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">aq_nab</span> <span class="op">&lt;-</span> <span class="fu">nabular</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="va">aq_s</span> <span class="op">&lt;-</span> <span class="fu"><a href="bind_shadow.html">bind_shadow</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/all.equal.html" class="external-link">all.equal</a></span><span class="op">(</span><span class="va">aq_nab</span>, <span class="va">aq_s</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] TRUE</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
-
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-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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diff --git a/docs/reference/naniar-ggproto.html b/docs/reference/naniar-ggproto.html
deleted file mode 100644
index c2679ed4..00000000
--- a/docs/reference/naniar-ggproto.html
+++ /dev/null
@@ -1,98 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="These are the stat and geom overrides using ggproto from ggplot2
-that make naniar work."><title>naniar-ggproto — GeomMissPoint • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="naniar-ggproto — GeomMissPoint"><meta property="og:description" content="These are the stat and geom overrides using ggproto from ggplot2
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-      <img src="../logo.png" class="logo" alt=""><h1>naniar-ggproto</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/geom-miss-point.R" class="external-link"><code>R/geom-miss-point.R</code></a>, <a href="https://github.com/njtierney/naniar/blob/HEAD/R/naniar-ggproto.R" class="external-link"><code>R/naniar-ggproto.R</code></a>, <a href="https://github.com/njtierney/naniar/blob/HEAD/R/stat-miss-point.R" class="external-link"><code>R/stat-miss-point.R</code></a></small>
-      <div class="d-none name"><code>naniar-ggproto.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>These are the stat and geom overrides using ggproto from ggplot2
-that make naniar work.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="va">StatMissPoint</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="format">Format<a class="anchor" aria-label="anchor" href="#format"></a></h2>
-    <p>An object of class <code>StatMissPoint</code> (inherits from <code>Stat</code>, <code>ggproto</code>, <code>gg</code>) of length 6.</p>
-    </div>
-
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diff --git a/docs/reference/naniar.html b/docs/reference/naniar.html
deleted file mode 100644
index cc9041d0..00000000
--- a/docs/reference/naniar.html
+++ /dev/null
@@ -1,99 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="naniar is a package to make it easier to summarise and handle missing values
-in R. It strives to do this in a way that is as consistent with tidyverse
-principles as possible.  The work is fully discussed at Tierney &amp;amp; Cook (2023)
-doi:10.18637/jss.v105.i07."><title>naniar — naniar • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="naniar — naniar"><meta property="og:description" content="naniar is a package to make it easier to summarise and handle missing values
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-<a href="doi:10.18637/jss.v105.i07">doi:10.18637/jss.v105.i07</a>.</p>
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-    <div class="dont-index"><p><code><a href="add_any_miss.html">add_any_miss()</a></code> <code><a href="add_label_missings.html">add_label_missings()</a></code> <code><a href="add_label_shadow.html">add_label_shadow()</a></code> <code><a href="add_miss_cluster.html">add_miss_cluster()</a></code> <code><a href="add_n_miss.html">add_n_miss()</a></code> <code><a href="add_prop_miss.html">add_prop_miss()</a></code> <code><a href="add_shadow.html">add_shadow()</a></code> <code><a href="add_shadow_shift.html">add_shadow_shift()</a></code> <code><a href="as_shadow.html">as_shadow()</a></code> <code><a href="bind_shadow.html">bind_shadow()</a></code> <code><a href="cast_shadow.html">cast_shadow()</a></code> <code><a href="cast_shadow_shift.html">cast_shadow_shift()</a></code> <code><a href="cast_shadow_shift_label.html">cast_shadow_shift_label()</a></code> <code><a href="draw_key.html">draw_key_missing_point()</a></code> <code><a href="gather_shadow.html">gather_shadow()</a></code> <code><a href="geom_miss_point.html">geom_miss_point()</a></code> <code><a href="gg_miss_case.html">gg_miss_case()</a></code> <code><a href="gg_miss_case_cumsum.html">gg_miss_case_cumsum()</a></code> <code><a href="gg_miss_fct.html">gg_miss_fct()</a></code> <code><a href="gg_miss_span.html">gg_miss_span()</a></code> <code><a href="gg_miss_var.html">gg_miss_var()</a></code> <code><a href="gg_miss_var_cumsum.html">gg_miss_var_cumsum()</a></code> <code><a href="gg_miss_which.html">gg_miss_which()</a></code> <code><a href="label_miss_1d.html">label_miss_1d()</a></code> <code><a href="label_miss_2d.html">label_miss_2d()</a></code> <code><a href="label_missings.html">label_missings()</a></code> <code><a href="pct-miss-complete-case.html">pct_miss_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_miss_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_miss_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_miss_var()</a></code> <code><a href="pct-miss-complete-case.html">pct_complete_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_complete_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_complete_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_complete_var()</a></code> <code><a href="miss_prop_summary.html">miss_prop_summary()</a></code> <code><a href="miss_case_summary.html">miss_case_summary()</a></code> <code><a href="miss_case_table.html">miss_case_table()</a></code> <code><a href="miss_summary.html">miss_summary()</a></code> <code><a href="miss-pct-prop-defunct.html">miss_var_prop()</a></code> <code><a href="miss_var_run.html">miss_var_run()</a></code> <code><a href="miss_var_span.html">miss_var_span()</a></code> <code><a href="miss_var_summary.html">miss_var_summary()</a></code> <code><a href="miss_var_table.html">miss_var_table()</a></code> <code><a href="n_complete.html">n_complete()</a></code> <code><a href="n_complete_row.html">n_complete_row()</a></code> <code><a href="n_miss.html">n_miss()</a></code> <code><a href="n_miss_row.html">n_miss_row()</a></code> <code><a href="pct_complete.html">pct_complete()</a></code> <code><a href="pct_miss.html">pct_miss()</a></code> <code><a href="prop_complete.html">prop_complete()</a></code> <code><a href="prop_complete_row.html">prop_complete_row()</a></code> <code><a href="prop_miss.html">prop_miss()</a></code> <code><a href="prop_miss_row.html">prop_miss_row()</a></code> <code><a href="replace_to_na.html">replace_to_na()</a></code> <code><a href="replace_with_na.html">replace_with_na()</a></code> <code><a href="replace_with_na_all.html">replace_with_na_all()</a></code> <code><a href="replace_with_na_at.html">replace_with_na_at()</a></code> <code><a href="replace_with_na_if.html">replace_with_na_if()</a></code> <code><a href="shadow_shift.html">shadow_shift()</a></code> <code><a href="stat_miss_point.html">stat_miss_point()</a></code> <code><a href="https://docs.ropensci.org/visdat/reference/vis_miss.html" class="external-link">vis_miss()</a></code> <code><a href="where_na.html">where_na()</a></code></p></div>
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-
-    
-    <p>These are the stat and geom overrides using ggproto from ggplot2 that make narnia work.</p>
-    
-
-    <pre class="usage"><span class='no'>StatMissingPoint</span></pre>
-        
-    <h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
-
-    <p>An object of class <code>StatMissingPoint</code> (inherits from <code>Stat</code>, <code>ggproto</code>, <code>gg</code>) of length 6.</p>
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-in R. It strives to do this in a way that is as consistent with tidyverse
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diff --git a/docs/reference/new_nabular.html b/docs/reference/new_nabular.html
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-    </tr>
-    <tr>
-      <th>extra_levels</th>
-      <td><p>the extra levels to give to <code>shade</code> objects, such as "broken_machine" and so on, which get converted into "NA_broken_machine".</p></td>
-    </tr>
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diff --git a/docs/reference/new_shadow.html b/docs/reference/new_shadow.html
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diff --git a/docs/reference/oceanbuoys.html b/docs/reference/oceanbuoys.html
deleted file mode 100644
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--- a/docs/reference/oceanbuoys.html
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-and prediction of El Ni'o and La Ni'a. The data is collected by the
-Tropical Atmosphere Ocean project
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-and prediction of El Ni'o and La Ni'a. The data is collected by the
-Tropical Atmosphere Ocean project
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-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>West Pacific Tropical Atmosphere Ocean Data, 1993 &amp; 1997.</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/data-oceanbuoys.R" class="external-link"><code>R/data-oceanbuoys.R</code></a></small>
-      <div class="d-none name"><code>oceanbuoys.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Real-time data from moored ocean buoys for improved detection, understanding
-and prediction of El Ni'o and La Ni'a. The data is collected by the
-Tropical Atmosphere Ocean project
-(<a href="https://www.pmel.noaa.gov/gtmba/pmel-theme/pacific-ocean-tao" class="external-link">https://www.pmel.noaa.gov/gtmba/pmel-theme/pacific-ocean-tao</a>).</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu"><a href="https://rdrr.io/r/utils/data.html" class="external-link">data</a></span><span class="op">(</span><span class="va">oceanbuoys</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="format">Format<a class="anchor" aria-label="anchor" href="#format"></a></h2>
-    <p>An object of class <code>tbl_df</code> (inherits from <code>tbl</code>, <code>data.frame</code>) with 736 rows and 8 columns.</p>
-    </div>
-    <div class="section level2">
-    <h2 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a></h2>
-    <p><a href="https://www.pmel.noaa.gov/tao/drupal/disdel/" class="external-link">https://www.pmel.noaa.gov/tao/drupal/disdel/</a></p>
-    </div>
-    <div class="section level2">
-    <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
-    <p>Format: a data frame with 736 observations on the following 8
-variables.</p><dl><dt><code>year</code></dt>
-<dd><p>A numeric with levels <code>1993</code> <code>1997</code>.</p></dd>
-
-<dt><code>latitude</code></dt>
-<dd><p>A numeric with levels <code>-5</code>  <code>-2</code> <code>0</code>.</p></dd>
-
-<dt><code>longitude</code></dt>
-<dd><p>A numeric with levels <code>-110</code> <code>-95</code>.</p></dd>
-
-<dt><code>sea_temp_c</code></dt>
-<dd><p>Sea surface temperature(degree Celsius),  measured
-by the TAO buoys at one meter below the surface.</p></dd>
-
-<dt><code>air_temp_c</code></dt>
-<dd><p>Air temperature(degree Celsius), measured by the
-TAO buoys three meters above the sea surface.</p></dd>
-
-<dt><code>humidity</code></dt>
-<dd><p>Relative humidity(%), measured by the TAO buoys 3
-meters above the sea surface.</p></dd>
-
-<dt><code>wind_ew</code></dt>
-<dd><p>The East-West wind vector components(M/s).  TAO buoys
-measure the wind speed and direction four meters above the sea surface.
-If it is positive, the East-West component of the wind is blowing towards
-the East. If it is negative, this component is blowing towards the West.</p></dd>
-
-<dt><code>wind_ns</code></dt>
-<dd><p>The North-South wind vector components(M/s). TAO
-buoys measure the wind speed and direction four meters above the sea
-surface. If it is positive, the North-South component of the wind is
-blowing towards the North. If it is negative, this component is blowing
-towards the South.</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p>library(MissingDataGUI) (data named "tao")</p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu"><a href="https://docs.ropensci.org/visdat/reference/vis_miss.html" class="external-link">vis_miss</a></span><span class="op">(</span><span class="va">oceanbuoys</span><span class="op">)</span></span></span>
-<span class="r-plt img"><img src="oceanbuoys-1.png" alt="" width="700" height="433"></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># Look at the missingness in the variables</span></span></span>
-<span class="r-in"><span><span class="fu"><a href="miss_var_summary.html">miss_var_summary</a></span><span class="op">(</span><span class="va">oceanbuoys</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 8 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   variable   n_miss pct_miss</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>       <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> humidity       93   12.6  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> air_temp_c     81   11.0  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> sea_temp_c      3    0.408</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span> year            0    0    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span> latitude        0    0    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">6</span> longitude       0    0    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">7</span> wind_ew         0    0    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">8</span> wind_ns         0    0    </span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="co"># Look at the missingness in air temperature and humidity</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="va">p</span> <span class="op">&lt;-</span></span></span>
-<span class="r-in"><span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">oceanbuoys</span>,</span></span>
-<span class="r-in"><span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">air_temp_c</span>,</span></span>
-<span class="r-in"><span>           y <span class="op">=</span> <span class="va">humidity</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span></span>
-<span class="r-in"><span>     <span class="fu"><a href="geom_miss_point.html">geom_miss_point</a></span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span> <span class="va">p</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span> <span class="co"># for each year?</span></span></span>
-<span class="r-in"><span> <span class="va">p</span> <span class="op">+</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/facet_wrap.html" class="external-link">facet_wrap</a></span><span class="op">(</span><span class="op">~</span><span class="va">year</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span> <span class="co"># this shows that there are more missing values in humidity in 1993, and</span></span></span>
-<span class="r-in"><span> <span class="co"># more air temperature missing values in 1997</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span> <span class="co"># see more examples in the vignette, "getting started with naniar".</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
-
-
-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
-</div>
-
-<div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
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diff --git a/docs/reference/pct-miss-complete-case.html b/docs/reference/pct-miss-complete-case.html
deleted file mode 100644
index 0c0e0c33..00000000
--- a/docs/reference/pct-miss-complete-case.html
+++ /dev/null
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-<!DOCTYPE html>
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-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Percentage of cases that contain a missing or complete values.</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/prop-pct-var-case-miss-complete.R" class="external-link"><code>R/prop-pct-var-case-miss-complete.R</code></a></small>
-      <div class="d-none name"><code>pct-miss-complete-case.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Calculate the percentage of cases (rows) that contain a missing or complete
-value.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">pct_miss_case</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">pct_complete_case</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>a dataframe</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>numeric the percentage of cases that contain a missing or complete
-value</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code>pct_miss_case()</code> <code><a href="prop-miss-complete-case.html">prop_miss_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_miss_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_miss_var()</a></code> <code>pct_complete_case()</code> <code><a href="prop-miss-complete-case.html">prop_complete_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_complete_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_complete_var()</a></code> <code><a href="miss_prop_summary.html">miss_prop_summary()</a></code> <code><a href="miss_case_summary.html">miss_case_summary()</a></code> <code><a href="miss_case_table.html">miss_case_table()</a></code> <code><a href="miss_summary.html">miss_summary()</a></code> <code><a href="miss-pct-prop-defunct.html">miss_var_prop()</a></code> <code><a href="miss_var_run.html">miss_var_run()</a></code> <code><a href="miss_var_span.html">miss_var_span()</a></code> <code><a href="miss_var_summary.html">miss_var_summary()</a></code> <code><a href="miss_var_table.html">miss_var_table()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">pct_miss_case</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 27.45098</span>
-<span class="r-in"><span><span class="fu">pct_complete_case</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 72.54902</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
-
-
-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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diff --git a/docs/reference/pct-miss-complete-var.html b/docs/reference/pct-miss-complete-var.html
deleted file mode 100644
index 27d43daf..00000000
--- a/docs/reference/pct-miss-complete-var.html
+++ /dev/null
@@ -1,123 +0,0 @@
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-      <img src="../logo.png" class="logo" alt=""><h1>Percentage of variables containing missings or complete values</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/prop-pct-var-case-miss-complete.R" class="external-link"><code>R/prop-pct-var-case-miss-complete.R</code></a></small>
-      <div class="d-none name"><code>pct-miss-complete-var.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Calculate the percentage of variables that contain a single missing or
-complete value.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">pct_miss_var</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">pct_complete_var</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>a dataframe</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>numeric the percent of variables that contain missing or complete
-data</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="pct-miss-complete-case.html">pct_miss_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_miss_case()</a></code> <code>pct_miss_var()</code> <code><a href="prop-miss-complete-var.html">prop_miss_var()</a></code> <code><a href="pct-miss-complete-case.html">pct_complete_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_complete_case()</a></code> <code>pct_complete_var()</code> <code><a href="prop-miss-complete-var.html">prop_complete_var()</a></code> <code><a href="miss_prop_summary.html">miss_prop_summary()</a></code> <code><a href="miss_case_summary.html">miss_case_summary()</a></code> <code><a href="miss_case_table.html">miss_case_table()</a></code> <code><a href="miss_summary.html">miss_summary()</a></code> <code><a href="miss-pct-prop-defunct.html">miss_var_prop()</a></code> <code><a href="miss_var_run.html">miss_var_run()</a></code> <code><a href="miss_var_span.html">miss_var_span()</a></code> <code><a href="miss_var_summary.html">miss_var_summary()</a></code> <code><a href="miss_var_table.html">miss_var_table()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu"><a href="prop-miss-complete-var.html">prop_miss_var</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.3333333</span>
-<span class="r-in"><span><span class="fu"><a href="prop-miss-complete-var.html">prop_complete_var</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.6666667</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/pct_complete.html b/docs/reference/pct_complete.html
deleted file mode 100644
index 1333d3d0..00000000
--- a/docs/reference/pct_complete.html
+++ /dev/null
@@ -1,113 +0,0 @@
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-      <img src="../logo.png" class="logo" alt=""><h1>Return the percent of complete values</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/n-prop-miss-complete.R" class="external-link"><code>R/n-prop-miss-complete.R</code></a></small>
-      <div class="d-none name"><code>pct_complete.Rd</code></div>
-    </div>
-
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-    <p>The complement to <code>pct_miss</code></p>
-    </div>
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-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">pct_complete</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
-<dd><p>vector or data.frame</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>numeric percent of complete values</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">pct_complete</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 95.20697</span>
-<span class="r-in"><span><span class="fu">pct_complete</span><span class="op">(</span><span class="va">airquality</span><span class="op">$</span><span class="va">Ozone</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 75.81699</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/pct_miss.html b/docs/reference/pct_miss.html
deleted file mode 100644
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+++ /dev/null
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-      <img src="../logo.png" class="logo" alt=""><h1>Return the percent of missing values</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/n-prop-miss-complete.R" class="external-link"><code>R/n-prop-miss-complete.R</code></a></small>
-      <div class="d-none name"><code>pct_miss.Rd</code></div>
-    </div>
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-    <div class="ref-description section level2">
-    <p>This is shorthand for <code>mean(is.na(x)) * 100</code></p>
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-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">pct_miss</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span></code></pre></div>
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-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
-<dd><p>vector or data.frame</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>numeric the percent of missing values in x</p>
-    </div>
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-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">pct_miss</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 4.793028</span>
-<span class="r-in"><span><span class="fu">pct_miss</span><span class="op">(</span><span class="va">airquality</span><span class="op">$</span><span class="va">Ozone</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 24.18301</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/pedestrian.html b/docs/reference/pedestrian.html
deleted file mode 100644
index bf3e156e..00000000
--- a/docs/reference/pedestrian.html
+++ /dev/null
@@ -1,171 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="This dataset contains hourly counts of pedestrians from 4 sensors around
-Melbourne: Birrarung Marr, Bourke Street Mall, Flagstaff station, and
-Spencer St-Collins St (south), recorded from January 1st 2016 at 00:00:00
-to December 31st 2016 at 23:00:00. The data is made free and publicly
-available from https://data.melbourne.vic.gov.au/explore/dataset/pedestrian-counting-system-monthly-counts-per-hour/information/"><title>Pedestrian count information around Melbourne for 2016 — pedestrian • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Pedestrian count information around Melbourne for 2016 — pedestrian"><meta property="og:description" content="This dataset contains hourly counts of pedestrians from 4 sensors around
-Melbourne: Birrarung Marr, Bourke Street Mall, Flagstaff station, and
-Spencer St-Collins St (south), recorded from January 1st 2016 at 00:00:00
-to December 31st 2016 at 23:00:00. The data is made free and publicly
-available from https://data.melbourne.vic.gov.au/explore/dataset/pedestrian-counting-system-monthly-counts-per-hour/information/"><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-<div class="row">
-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Pedestrian count information around Melbourne for 2016</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/data-pedestrian.R" class="external-link"><code>R/data-pedestrian.R</code></a></small>
-      <div class="d-none name"><code>pedestrian.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>This dataset contains hourly counts of pedestrians from 4 sensors around
-Melbourne: Birrarung Marr, Bourke Street Mall, Flagstaff station, and
-Spencer St-Collins St (south), recorded from January 1st 2016 at 00:00:00
-to December 31st 2016 at 23:00:00. The data is made free and publicly
-available from <a href="https://data.melbourne.vic.gov.au/explore/dataset/pedestrian-counting-system-monthly-counts-per-hour/information/" class="external-link">https://data.melbourne.vic.gov.au/explore/dataset/pedestrian-counting-system-monthly-counts-per-hour/information/</a></p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu"><a href="https://rdrr.io/r/utils/data.html" class="external-link">data</a></span><span class="op">(</span><span class="va">pedestrian</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="format">Format<a class="anchor" aria-label="anchor" href="#format"></a></h2>
-    <p>A tibble with 37,700 rows and 9 variables:</p><dl><dt>hourly_counts</dt>
-<dd><p>(integer) the number of pedestrians counted at that sensor
-at that time</p></dd>
-
-<dt>date_time</dt>
-<dd><p>(POSIXct, POSIXt) The time that the count was taken</p></dd>
-
-<dt>year</dt>
-<dd><p>(integer) Year of record</p></dd>
-
-<dt>month</dt>
-<dd><p>(factor) Month of record as an ordered factor (1 = January, 12 =
-December)</p></dd>
-
-<dt>month_day</dt>
-<dd><p>(integer) Full day of the month</p></dd>
-
-<dt>week_day</dt>
-<dd><p>(factor) Full day of the week as an ordered factor (1 = Sunday,
-7 = Saturday)</p></dd>
-
-<dt>hour</dt>
-<dd><p>(integer) The hour of the day in 24 hour format</p></dd>
-
-<dt>sensor_id</dt>
-<dd><p>(integer) the id of the sensor</p></dd>
-
-<dt>sensor_name</dt>
-<dd><p>(character) the full name of the sensor</p></dd>
-
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a></h2>
-    <p><a href="https://data.melbourne.vic.gov.au/explore/dataset/pedestrian-counting-system-monthly-counts-per-hour/information/" class="external-link">https://data.melbourne.vic.gov.au/explore/dataset/pedestrian-counting-system-monthly-counts-per-hour/information/</a></p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># explore the missingness with vis_miss</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu"><a href="https://docs.ropensci.org/visdat/reference/vis_miss.html" class="external-link">vis_miss</a></span><span class="op">(</span><span class="va">pedestrian</span><span class="op">)</span></span></span>
-<span class="r-plt img"><img src="pedestrian-1.png" alt="" width="700" height="433"></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># Look at the missingness in the variables</span></span></span>
-<span class="r-in"><span><span class="fu"><a href="miss_var_summary.html">miss_var_summary</a></span><span class="op">(</span><span class="va">pedestrian</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 9 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   variable      n_miss pct_miss</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>          <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> hourly_counts   <span style="text-decoration: underline;">2</span>548     6.76</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> date_time          0     0   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> year               0     0   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span> month              0     0   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span> month_day          0     0   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">6</span> week_day           0     0   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">7</span> hour               0     0   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">8</span> sensor_id          0     0   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">9</span> sensor_name        0     0   </span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="co"># There is only missingness in hourly_counts</span></span></span>
-<span class="r-in"><span><span class="co"># Look at the missingness over a rolling window</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="fu"><a href="gg_miss_span.html">gg_miss_span</a></span><span class="op">(</span><span class="va">pedestrian</span>, <span class="va">hourly_counts</span>, span_every <span class="op">=</span> <span class="fl">3000</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
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diff --git a/docs/reference/percent_missing_case.html b/docs/reference/percent_missing_case.html
deleted file mode 100644
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-    <h1>Percentage of cases that contain a missing values.</h1>
-    </div>
-
-    
-    <p>Deprecated as of version 0.0.6.9000. Please use miss_case_pct instead.</p>
-    
-
-    <pre class="usage"><span class='fu'>percent_missing_case</span>(<span class='no'>...</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a> Arguments</h2>
-    <table class="ref-arguments">
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-
-    <p>miss_case_pct</p>
-    
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-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
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diff --git a/docs/reference/percent_missing_df.html b/docs/reference/percent_missing_df.html
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-    <h1>Percentage of missing data in a dataframe</h1>
-    </div>
-
-    
-    <p>Deprecated as of version 0.0.6.9000. Please use miss_df_pct instead.</p>
-    
-
-    <pre class="usage"><span class='fu'>percent_missing_df</span>(<span class='no'>...</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a> Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>...</th>
-      <td><p>so that users can still receive meaningful error</p></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <p>miss_df_pct</p>
-    
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-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
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-      
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diff --git a/docs/reference/percent_missing_var.html b/docs/reference/percent_missing_var.html
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-    </div>
-
-    
-    <p>Deprecated as of version 0.0.6.9000. Please use miss_var_pct instead.</p>
-    
-
-    <pre class="usage"><span class='fu'>percent_missing_var</span>(<span class='no'>...</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a> Arguments</h2>
-    <table class="ref-arguments">
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diff --git a/docs/reference/plotly_helpers.html b/docs/reference/plotly_helpers.html
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-      <div class="d-none name"><code>plotly_helpers.Rd</code></div>
-    </div>
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-    <p>Helper functions to make it easier to automatically create
-plotly charts. This function makes it possible to convert ggplot2 geoms
-that are not included with ggplot2 itself. Users shouldn't need to use this
-function. It exists purely to allow other package authors to write their
-own conversion method(s).</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">to_basic.GeomMissPoint</span><span class="op">(</span><span class="va">data</span>, <span class="va">prestats_data</span>, <span class="va">layout</span>, <span class="va">params</span>, <span class="va">p</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
-    </div>
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-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>the data returned by <code><a href="https://ggplot2.tidyverse.org/reference/ggplot_build.html" class="external-link">ggplot2::ggplot_build()</a></code>.</p></dd>
-
-
-<dt>prestats_data</dt>
-<dd><p>the data before statistics are computed.</p></dd>
-
-
-<dt>layout</dt>
-<dd><p>the panel layout.</p></dd>
-
-
-<dt>params</dt>
-<dd><p>parameters for the geom, statistic, and 'constant' aesthetics</p></dd>
-
-
-<dt>p</dt>
-<dd><p>a ggplot2 object (the conversion may depend on scales, for
-instance).</p></dd>
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-
-<dt>...</dt>
-<dd><p>currently ignored</p></dd>
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diff --git a/docs/reference/prop-miss-complete-case.html b/docs/reference/prop-miss-complete-case.html
deleted file mode 100644
index a3a95aa2..00000000
--- a/docs/reference/prop-miss-complete-case.html
+++ /dev/null
@@ -1,123 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Calculate the proportion of cases (rows) that contain missing or complete
-values."><title>Proportion of cases that contain a missing or complete values. — prop-miss-complete-case • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Proportion of cases that contain a missing or complete values. — prop-miss-complete-case"><meta property="og:description" content="Calculate the proportion of cases (rows) that contain missing or complete
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-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/prop-pct-var-case-miss-complete.R" class="external-link"><code>R/prop-pct-var-case-miss-complete.R</code></a></small>
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-    <p>Calculate the proportion of cases (rows) that contain missing or complete
-values.</p>
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-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">prop_miss_case</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">prop_complete_case</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>a dataframe</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>numeric the proportion of cases that contain a missing or complete
-value</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="pct-miss-complete-case.html">pct_miss_case()</a></code> <code>prop_miss_case()</code> <code><a href="pct-miss-complete-var.html">pct_miss_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_miss_var()</a></code> <code><a href="pct-miss-complete-case.html">pct_complete_case()</a></code> <code>prop_complete_case()</code> <code><a href="pct-miss-complete-var.html">pct_complete_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_complete_var()</a></code> <code><a href="miss_prop_summary.html">miss_prop_summary()</a></code> <code><a href="miss_case_summary.html">miss_case_summary()</a></code> <code><a href="miss_case_table.html">miss_case_table()</a></code> <code><a href="miss_summary.html">miss_summary()</a></code> <code><a href="miss-pct-prop-defunct.html">miss_var_prop()</a></code> <code><a href="miss_var_run.html">miss_var_run()</a></code> <code><a href="miss_var_span.html">miss_var_span()</a></code> <code><a href="miss_var_summary.html">miss_var_summary()</a></code> <code><a href="miss_var_table.html">miss_var_table()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">prop_miss_case</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.2745098</span>
-<span class="r-in"><span><span class="fu">prop_complete_case</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.7254902</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
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diff --git a/docs/reference/prop-miss-complete-var.html b/docs/reference/prop-miss-complete-var.html
deleted file mode 100644
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--- a/docs/reference/prop-miss-complete-var.html
+++ /dev/null
@@ -1,123 +0,0 @@
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-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Calculate the proportion of variables that contain a single missing or
-complete values."><title>Proportion of variables containing missings or complete values — prop-miss-complete-var • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Proportion of variables containing missings or complete values — prop-miss-complete-var"><meta property="og:description" content="Calculate the proportion of variables that contain a single missing or
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-      <img src="../logo.png" class="logo" alt=""><h1>Proportion of variables containing missings or complete values</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/prop-pct-var-case-miss-complete.R" class="external-link"><code>R/prop-pct-var-case-miss-complete.R</code></a></small>
-      <div class="d-none name"><code>prop-miss-complete-var.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Calculate the proportion of variables that contain a single missing or
-complete values.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">prop_miss_var</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">prop_complete_var</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>a dataframe</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>numeric the proportion of variables that contain missing or complete
-data</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="pct-miss-complete-case.html">pct_miss_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_miss_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_miss_var()</a></code> <code>prop_miss_var()</code> <code><a href="pct-miss-complete-case.html">pct_complete_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_complete_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_complete_var()</a></code> <code>prop_complete_var()</code> <code><a href="miss_prop_summary.html">miss_prop_summary()</a></code> <code><a href="miss_case_summary.html">miss_case_summary()</a></code> <code><a href="miss_case_table.html">miss_case_table()</a></code> <code><a href="miss_summary.html">miss_summary()</a></code> <code><a href="miss-pct-prop-defunct.html">miss_var_prop()</a></code> <code><a href="miss_var_run.html">miss_var_run()</a></code> <code><a href="miss_var_span.html">miss_var_span()</a></code> <code><a href="miss_var_summary.html">miss_var_summary()</a></code> <code><a href="miss_var_table.html">miss_var_table()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">prop_miss_var</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.3333333</span>
-<span class="r-in"><span><span class="fu">prop_complete_var</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.6666667</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
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diff --git a/docs/reference/prop_complete.html b/docs/reference/prop_complete.html
deleted file mode 100644
index 47392f14..00000000
--- a/docs/reference/prop_complete.html
+++ /dev/null
@@ -1,113 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="The complement to prop_miss"><title>Return the proportion of complete values — prop_complete • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Return the proportion of complete values — prop_complete"><meta property="og:description" content="The complement to prop_miss"><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Return the proportion of complete values</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/n-prop-miss-complete.R" class="external-link"><code>R/n-prop-miss-complete.R</code></a></small>
-      <div class="d-none name"><code>prop_complete.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>The complement to <code>prop_miss</code></p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">prop_complete</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
-<dd><p>vector or data.frame</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>numeric proportion of complete values</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">prop_complete</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.9520697</span>
-<span class="r-in"><span><span class="fu">prop_complete</span><span class="op">(</span><span class="va">airquality</span><span class="op">$</span><span class="va">Ozone</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.7581699</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
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diff --git a/docs/reference/prop_complete_row.html b/docs/reference/prop_complete_row.html
deleted file mode 100644
index 4865a98e..00000000
--- a/docs/reference/prop_complete_row.html
+++ /dev/null
@@ -1,139 +0,0 @@
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-      <img src="../logo.png" class="logo" alt=""><h1>Return a vector of the proportion of missing values in each row</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/n-prop-miss-complete-rows.R" class="external-link"><code>R/n-prop-miss-complete-rows.R</code></a></small>
-      <div class="d-none name"><code>prop_complete_row.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Substitute for <code>rowMeans(!is.na(data))</code>, but it also checks if input is NULL or
-is a dataframe</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">prop_complete_row</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>a dataframe</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>numeric vector of the proportion of missing values in each row</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="pct-miss-complete-case.html">pct_miss_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_miss_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_miss_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_miss_var()</a></code> <code><a href="pct-miss-complete-case.html">pct_complete_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_complete_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_complete_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_complete_var()</a></code> <code><a href="miss_prop_summary.html">miss_prop_summary()</a></code> <code><a href="miss_case_summary.html">miss_case_summary()</a></code> <code><a href="miss_case_table.html">miss_case_table()</a></code> <code><a href="miss_summary.html">miss_summary()</a></code> <code><a href="miss-pct-prop-defunct.html">miss_var_prop()</a></code> <code><a href="miss_var_run.html">miss_var_run()</a></code> <code><a href="miss_var_span.html">miss_var_span()</a></code> <code><a href="miss_var_summary.html">miss_var_summary()</a></code> <code><a href="miss_var_table.html">miss_var_table()</a></code> <code><a href="n_complete.html">n_complete()</a></code> <code><a href="n_complete_row.html">n_complete_row()</a></code> <code><a href="n_miss.html">n_miss()</a></code> <code><a href="n_miss_row.html">n_miss_row()</a></code> <code><a href="pct_complete.html">pct_complete()</a></code> <code><a href="pct_miss.html">pct_miss()</a></code> <code><a href="prop_complete.html">prop_complete()</a></code> <code>prop_complete_row()</code> <code><a href="prop_miss.html">prop_miss()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">prop_complete_row</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   [1] 1.0000000 1.0000000 1.0000000 1.0000000 0.6666667 0.8333333 1.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   [8] 1.0000000 1.0000000 0.8333333 0.8333333 1.0000000 1.0000000 1.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [15] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [22] 1.0000000 1.0000000 1.0000000 0.8333333 0.8333333 0.6666667 1.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [29] 1.0000000 1.0000000 1.0000000 0.8333333 0.8333333 0.8333333 0.8333333</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [36] 0.8333333 0.8333333 1.0000000 0.8333333 1.0000000 1.0000000 0.8333333</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [43] 0.8333333 1.0000000 0.8333333 0.8333333 1.0000000 1.0000000 1.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [50] 1.0000000 1.0000000 0.8333333 0.8333333 0.8333333 0.8333333 0.8333333</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [57] 0.8333333 0.8333333 0.8333333 0.8333333 0.8333333 1.0000000 1.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [64] 1.0000000 0.8333333 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [71] 1.0000000 0.8333333 1.0000000 1.0000000 0.8333333 1.0000000 1.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [78] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 0.8333333 0.8333333</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [85] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [92] 1.0000000 1.0000000 1.0000000 1.0000000 0.8333333 0.8333333 0.8333333</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [99] 1.0000000 1.0000000 1.0000000 0.8333333 0.8333333 1.0000000 1.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [106] 1.0000000 0.8333333 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [113] 1.0000000 1.0000000 0.8333333 1.0000000 1.0000000 1.0000000 0.8333333</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [120] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [127] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [134] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [141] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [148] 1.0000000 1.0000000 0.8333333 1.0000000 1.0000000 1.0000000</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
-
-
-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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diff --git a/docs/reference/prop_miss.html b/docs/reference/prop_miss.html
deleted file mode 100644
index 545dfbe4..00000000
--- a/docs/reference/prop_miss.html
+++ /dev/null
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-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">prop_miss</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span></code></pre></div>
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-<dd><p>vector or data.frame</p></dd>
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-</dl></div>
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-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>numeric the proportion of missing values in x</p>
-    </div>
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-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">prop_miss</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.04793028</span>
-<span class="r-in"><span><span class="fu">prop_miss</span><span class="op">(</span><span class="va">airquality</span><span class="op">$</span><span class="va">Ozone</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.2418301</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/prop_miss_row.html b/docs/reference/prop_miss_row.html
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+++ /dev/null
@@ -1,139 +0,0 @@
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-      <img src="../logo.png" class="logo" alt=""><h1>Return a vector of the proportion of missing values in each row</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/n-prop-miss-complete-rows.R" class="external-link"><code>R/n-prop-miss-complete-rows.R</code></a></small>
-      <div class="d-none name"><code>prop_miss_row.Rd</code></div>
-    </div>
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-    <div class="ref-description section level2">
-    <p>Substitute for <code>rowMeans(is.na(data))</code>, but it also checks if input is NULL or
-is a dataframe</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">prop_miss_row</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>a dataframe</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>numeric vector of the proportion of missing values in each row</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="pct-miss-complete-case.html">pct_miss_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_miss_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_miss_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_miss_var()</a></code> <code><a href="pct-miss-complete-case.html">pct_complete_case()</a></code> <code><a href="prop-miss-complete-case.html">prop_complete_case()</a></code> <code><a href="pct-miss-complete-var.html">pct_complete_var()</a></code> <code><a href="prop-miss-complete-var.html">prop_complete_var()</a></code> <code><a href="miss_prop_summary.html">miss_prop_summary()</a></code> <code><a href="miss_case_summary.html">miss_case_summary()</a></code> <code><a href="miss_case_table.html">miss_case_table()</a></code> <code><a href="miss_summary.html">miss_summary()</a></code> <code><a href="miss-pct-prop-defunct.html">miss_var_prop()</a></code> <code><a href="miss_var_run.html">miss_var_run()</a></code> <code><a href="miss_var_span.html">miss_var_span()</a></code> <code><a href="miss_var_summary.html">miss_var_summary()</a></code> <code><a href="miss_var_table.html">miss_var_table()</a></code> <code><a href="n_complete.html">n_complete()</a></code> <code><a href="n_complete_row.html">n_complete_row()</a></code> <code><a href="n_miss.html">n_miss()</a></code> <code><a href="n_miss_row.html">n_miss_row()</a></code> <code><a href="pct_complete.html">pct_complete()</a></code> <code><a href="pct_miss.html">pct_miss()</a></code> <code><a href="prop_complete.html">prop_complete()</a></code> <code><a href="prop_complete_row.html">prop_complete_row()</a></code> <code><a href="prop_miss.html">prop_miss()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">prop_miss_row</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   [1] 0.0000000 0.0000000 0.0000000 0.0000000 0.3333333 0.1666667 0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   [8] 0.0000000 0.0000000 0.1666667 0.1666667 0.0000000 0.0000000 0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [15] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [22] 0.0000000 0.0000000 0.0000000 0.1666667 0.1666667 0.3333333 0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [29] 0.0000000 0.0000000 0.0000000 0.1666667 0.1666667 0.1666667 0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [36] 0.1666667 0.1666667 0.0000000 0.1666667 0.0000000 0.0000000 0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [43] 0.1666667 0.0000000 0.1666667 0.1666667 0.0000000 0.0000000 0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [50] 0.0000000 0.0000000 0.1666667 0.1666667 0.1666667 0.1666667 0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [57] 0.1666667 0.1666667 0.1666667 0.1666667 0.1666667 0.0000000 0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [64] 0.0000000 0.1666667 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [71] 0.0000000 0.1666667 0.0000000 0.0000000 0.1666667 0.0000000 0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [78] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.1666667 0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [85] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [92] 0.0000000 0.0000000 0.0000000 0.0000000 0.1666667 0.1666667 0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [99] 0.0000000 0.0000000 0.0000000 0.1666667 0.1666667 0.0000000 0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [106] 0.0000000 0.1666667 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [113] 0.0000000 0.0000000 0.1666667 0.0000000 0.0000000 0.0000000 0.1666667</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [148] 0.0000000 0.0000000 0.1666667 0.0000000 0.0000000 0.0000000</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
-
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-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
-</div>
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-<div class="pkgdown-footer-right">
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diff --git a/docs/reference/recode_shadow.html b/docs/reference/recode_shadow.html
deleted file mode 100644
index 3ae2b24f..00000000
--- a/docs/reference/recode_shadow.html
+++ /dev/null
@@ -1,157 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="It can be useful to add special missing values, naniar supports this with
-the recode_shadow function."><title>Add special missing values to the shadow matrix — recode_shadow • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Add special missing values to the shadow matrix — recode_shadow"><meta property="og:description" content="It can be useful to add special missing values, naniar supports this with
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-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Add special missing values to the shadow matrix</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/shadow-recode.R" class="external-link"><code>R/shadow-recode.R</code></a></small>
-      <div class="d-none name"><code>recode_shadow.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>It can be useful to add special missing values, naniar supports this with
-the <code>recode_shadow</code> function.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">recode_shadow</span><span class="op">(</span><span class="va">data</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="co"># S3 method for data.frame</span></span>
-<span><span class="fu">recode_shadow</span><span class="op">(</span><span class="va">data</span>, <span class="va">...</span><span class="op">)</span></span>
-<span></span>
-<span><span class="co"># S3 method for grouped_df</span></span>
-<span><span class="fu">recode_shadow</span><span class="op">(</span><span class="va">data</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>data.frame</p></dd>
-
-
-<dt>...</dt>
-<dd><p>A sequence of two-sided formulas as in dplyr::case_when,
-but when a wrapper function <code>.where</code> written around it.</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>a dataframe with altered shadows</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">df</span> <span class="op">&lt;-</span> <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/tribble.html" class="external-link">tribble</a></span><span class="op">(</span></span></span>
-<span class="r-in"><span><span class="op">~</span><span class="va">wind</span>, <span class="op">~</span><span class="va">temp</span>,</span></span>
-<span class="r-in"><span><span class="op">-</span><span class="fl">99</span>,    <span class="fl">45</span>,</span></span>
-<span class="r-in"><span><span class="fl">68</span>,    <span class="cn">NA</span>,</span></span>
-<span class="r-in"><span><span class="fl">72</span>,    <span class="fl">25</span></span></span>
-<span class="r-in"><span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">dfs</span> <span class="op">&lt;-</span> <span class="fu"><a href="bind_shadow.html">bind_shadow</a></span><span class="op">(</span><span class="va">df</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">dfs</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 3 × 4</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    wind  temp wind_NA temp_NA</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span>   -<span style="color: #BB0000;">99</span>    45 !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span>    68    <span style="color: #BB0000;">NA</span> !NA     NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span>    72    25 !NA     !NA    </span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">recode_shadow</span><span class="op">(</span><span class="va">dfs</span>, temp <span class="op">=</span> <span class="fu"><a href="where.html">.where</a></span><span class="op">(</span><span class="va">wind</span> <span class="op">==</span> <span class="op">-</span><span class="fl">99</span> <span class="op">~</span> <span class="st">"bananas"</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 3 × 4</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    wind  temp wind_NA temp_NA   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span>   -<span style="color: #BB0000;">99</span>    45 !NA     NA_bananas</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span>    68    <span style="color: #BB0000;">NA</span> !NA     NA        </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span>    72    25 !NA     !NA       </span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">recode_shadow</span><span class="op">(</span><span class="va">dfs</span>,</span></span>
-<span class="r-in"><span>              temp <span class="op">=</span> <span class="fu"><a href="where.html">.where</a></span><span class="op">(</span><span class="va">wind</span> <span class="op">==</span> <span class="op">-</span><span class="fl">99</span> <span class="op">~</span> <span class="st">"bananas"</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span><span class="fu">recode_shadow</span><span class="op">(</span>wind <span class="op">=</span> <span class="fu"><a href="where.html">.where</a></span><span class="op">(</span><span class="va">wind</span> <span class="op">==</span> <span class="op">-</span><span class="fl">99</span> <span class="op">~</span> <span class="st">"apples"</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 3 × 4</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    wind  temp wind_NA   temp_NA   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span>   -<span style="color: #BB0000;">99</span>    45 NA_apples NA_bananas</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span>    68    <span style="color: #BB0000;">NA</span> !NA       NA        </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span>    72    25 !NA       !NA       </span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
-
-
-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
-</div>
-
-<div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
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diff --git a/docs/reference/reexports.html b/docs/reference/reexports.html
deleted file mode 100644
index 8cf341f6..00000000
--- a/docs/reference/reexports.html
+++ /dev/null
@@ -1,129 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="These objects are imported from other packages. Follow the links
-below to see their documentation.
-
-  magrittr
-%&amp;gt;%
-
-
-  rlang
-are_na, is_na
-
-
-  visdat
-vis_miss
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-  magrittr
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-      <div class="d-none name"><code>reexports.Rd</code></div>
-    </div>
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-    <p>These objects are imported from other packages. Follow the links
-below to see their documentation.</p>
-<dl><dt>magrittr</dt>
-<dd><p><code>%&gt;%</code></p></dd>
-
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-  <dt>rlang</dt>
-<dd><p><code><a href="https://rlang.r-lib.org/reference/are_na.html" class="external-link">are_na</a></code>, <code><a href="https://rlang.r-lib.org/reference/are_na.html" class="external-link">is_na</a></code></p></dd>
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diff --git a/docs/reference/replace_to_na.html b/docs/reference/replace_to_na.html
deleted file mode 100644
index 5b3d69a4..00000000
--- a/docs/reference/replace_to_na.html
+++ /dev/null
@@ -1,103 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="This function is Defunct, please see replace_with_na()."><title>Replace values with missings — replace_to_na • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Replace values with missings — replace_to_na"><meta property="og:description" content="This function is Defunct, please see replace_with_na()."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-      <img src="../logo.png" class="logo" alt=""><h1>Replace values with missings</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/replace-to-na.R" class="external-link"><code>R/replace-to-na.R</code></a></small>
-      <div class="d-none name"><code>replace_to_na.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>This function is Defunct, please see <code><a href="replace_with_na.html">replace_with_na()</a></code>.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">replace_to_na</span><span class="op">(</span><span class="va">...</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>...</dt>
-<dd><p>additional arguments for methods.</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>values replaced by NA</p>
-    </div>
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-    </nav></aside></div>
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-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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diff --git a/docs/reference/replace_with_na.html b/docs/reference/replace_with_na.html
deleted file mode 100644
index 151adb97..00000000
--- a/docs/reference/replace_with_na.html
+++ /dev/null
@@ -1,164 +0,0 @@
-<!DOCTYPE html>
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-This is a complement to tidyr::replace_na."><title>Replace values with missings — replace_with_na • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Replace values with missings — replace_with_na"><meta property="og:description" content="Specify variables and their values that you want to convert to missing values.
-This is a complement to tidyr::replace_na."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-      <img src="../logo.png" class="logo" alt=""><h1>Replace values with missings</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/replace-with-na.R" class="external-link"><code>R/replace-with-na.R</code></a></small>
-      <div class="d-none name"><code>replace_with_na.Rd</code></div>
-    </div>
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-    <div class="ref-description section level2">
-    <p>Specify variables and their values that you want to convert to missing values.
-This is a complement to <code><a href="https://tidyr.tidyverse.org/reference/replace_na.html" class="external-link">tidyr::replace_na</a></code>.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">replace_with_na</span><span class="op">(</span><span class="va">data</span>, replace <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>A data.frame</p></dd>
-
-
-<dt>replace</dt>
-<dd><p>A named list given the NA to replace values for each column</p></dd>
-
-
-<dt>...</dt>
-<dd><p>additional arguments for methods. Currently unused</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>Dataframe with values replaced by NA.</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code>replace_with_na()</code> <code><a href="replace_with_na_all.html">replace_with_na_all()</a></code> <code><a href="replace_with_na_at.html">replace_with_na_at()</a></code> <code><a href="replace_with_na_if.html">replace_with_na_if()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">dat_ms</span> <span class="op">&lt;-</span> <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/tribble.html" class="external-link">tribble</a></span><span class="op">(</span><span class="op">~</span><span class="va">x</span>,  <span class="op">~</span><span class="va">y</span>,    <span class="op">~</span><span class="va">z</span>,</span></span>
-<span class="r-in"><span>                         <span class="fl">1</span>,   <span class="st">"A"</span>,   <span class="op">-</span><span class="fl">100</span>,</span></span>
-<span class="r-in"><span>                         <span class="fl">3</span>,   <span class="st">"N/A"</span>, <span class="op">-</span><span class="fl">99</span>,</span></span>
-<span class="r-in"><span>                         <span class="cn">NA</span>,  <span class="cn">NA</span>,    <span class="op">-</span><span class="fl">98</span>,</span></span>
-<span class="r-in"><span>                         <span class="op">-</span><span class="fl">99</span>, <span class="st">"E"</span>,   <span class="op">-</span><span class="fl">101</span>,</span></span>
-<span class="r-in"><span>                         <span class="op">-</span><span class="fl">98</span>, <span class="st">"F"</span>,   <span class="op">-</span><span class="fl">1</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">replace_with_na</span><span class="op">(</span><span class="va">dat_ms</span>,</span></span>
-<span class="r-in"><span>               replace <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>x <span class="op">=</span> <span class="op">-</span><span class="fl">99</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 5 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>       x y         z</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span>     1 A      -<span style="color: #BB0000;">100</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span>     3 N/A     -<span style="color: #BB0000;">99</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span>    <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span>      -<span style="color: #BB0000;">98</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span>    <span style="color: #BB0000;">NA</span> E      -<span style="color: #BB0000;">101</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span>   -<span style="color: #BB0000;">98</span> F        -<span style="color: #BB0000;">1</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">replace_with_na</span><span class="op">(</span><span class="va">dat_ms</span>,</span></span>
-<span class="r-in"><span>             replace <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>x <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="op">-</span><span class="fl">99</span>, <span class="op">-</span><span class="fl">98</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 5 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>       x y         z</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span>     1 A      -<span style="color: #BB0000;">100</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span>     3 N/A     -<span style="color: #BB0000;">99</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span>    <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span>      -<span style="color: #BB0000;">98</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span>    <span style="color: #BB0000;">NA</span> E      -<span style="color: #BB0000;">101</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span>    <span style="color: #BB0000;">NA</span> F        -<span style="color: #BB0000;">1</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">replace_with_na</span><span class="op">(</span><span class="va">dat_ms</span>,</span></span>
-<span class="r-in"><span>             replace <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>x <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="op">-</span><span class="fl">99</span>, <span class="op">-</span><span class="fl">98</span><span class="op">)</span>,</span></span>
-<span class="r-in"><span>                          y <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"N/A"</span><span class="op">)</span>,</span></span>
-<span class="r-in"><span>                          z <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="op">-</span><span class="fl">101</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 5 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>       x y         z</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span>     1 A      -<span style="color: #BB0000;">100</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span>     3 <span style="color: #BB0000;">NA</span>      -<span style="color: #BB0000;">99</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span>    <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span>      -<span style="color: #BB0000;">98</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span>    <span style="color: #BB0000;">NA</span> E        <span style="color: #BB0000;">NA</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span>    <span style="color: #BB0000;">NA</span> F        -<span style="color: #BB0000;">1</span></span>
-</code></pre></div>
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-      <img src="../logo.png" class="logo" alt=""><h1>Replace all values with NA where a certain condition is met</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/scoped-replace-with-na.R" class="external-link"><code>R/scoped-replace-with-na.R</code></a></small>
-      <div class="d-none name"><code>replace_with_na_all.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>This function takes a dataframe and replaces all values that meet the
-condition specified as an NA value, following a special syntax.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">replace_with_na_all</span><span class="op">(</span><span class="va">data</span>, <span class="va">condition</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>A dataframe</p></dd>
-
-
-<dt>condition</dt>
-<dd><p>A condition required to be TRUE to set NA. Here, the condition
-is specified with a formula, following the syntax: <code>~.x {condition}</code>.
-For example, writing <code>~.x &lt; 20</code> would mean "where a variable value is less
-than 20, replace with NA".</p></dd>
-
-</dl></div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">dat_ms</span> <span class="op">&lt;-</span> <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/tribble.html" class="external-link">tribble</a></span><span class="op">(</span><span class="op">~</span><span class="va">x</span>,  <span class="op">~</span><span class="va">y</span>,    <span class="op">~</span><span class="va">z</span>,</span></span>
-<span class="r-in"><span>                          <span class="fl">1</span>,   <span class="st">"A"</span>,   <span class="op">-</span><span class="fl">100</span>,</span></span>
-<span class="r-in"><span>                          <span class="fl">3</span>,   <span class="st">"N/A"</span>, <span class="op">-</span><span class="fl">99</span>,</span></span>
-<span class="r-in"><span>                          <span class="cn">NA</span>,  <span class="cn">NA</span>,    <span class="op">-</span><span class="fl">98</span>,</span></span>
-<span class="r-in"><span>                          <span class="op">-</span><span class="fl">99</span>, <span class="st">"E"</span>,   <span class="op">-</span><span class="fl">101</span>,</span></span>
-<span class="r-in"><span>                          <span class="op">-</span><span class="fl">98</span>, <span class="st">"F"</span>,   <span class="op">-</span><span class="fl">1</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">dat_ms</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 5 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>       x y         z</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span>     1 A      -<span style="color: #BB0000;">100</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span>     3 N/A     -<span style="color: #BB0000;">99</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span>    <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span>      -<span style="color: #BB0000;">98</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span>   -<span style="color: #BB0000;">99</span> E      -<span style="color: #BB0000;">101</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span>   -<span style="color: #BB0000;">98</span> F        -<span style="color: #BB0000;">1</span></span>
-<span class="r-in"><span><span class="co">#replace all instances of -99 with NA</span></span></span>
-<span class="r-in"><span><span class="fu">replace_with_na_all</span><span class="op">(</span>data <span class="op">=</span> <span class="va">dat_ms</span>,</span></span>
-<span class="r-in"><span>                    condition <span class="op">=</span> <span class="op">~</span><span class="va">.x</span> <span class="op">==</span> <span class="op">-</span><span class="fl">99</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 5 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>       x y         z</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span>     1 A      -<span style="color: #BB0000;">100</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span>     3 N/A      <span style="color: #BB0000;">NA</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span>    <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span>      -<span style="color: #BB0000;">98</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span>    <span style="color: #BB0000;">NA</span> E      -<span style="color: #BB0000;">101</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span>   -<span style="color: #BB0000;">98</span> F        -<span style="color: #BB0000;">1</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># replace all instances of -99 or -98, or "N/A" with NA</span></span></span>
-<span class="r-in"><span><span class="fu">replace_with_na_all</span><span class="op">(</span><span class="va">dat_ms</span>,</span></span>
-<span class="r-in"><span>                    condition <span class="op">=</span> <span class="op">~</span><span class="va">.x</span> <span class="op"><a href="https://rdrr.io/r/base/match.html" class="external-link">%in%</a></span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="op">-</span><span class="fl">99</span>, <span class="op">-</span><span class="fl">98</span>, <span class="st">"N/A"</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 5 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>       x y         z</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span>     1 A      -<span style="color: #BB0000;">100</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span>     3 <span style="color: #BB0000;">NA</span>       <span style="color: #BB0000;">NA</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span>    <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span>       <span style="color: #BB0000;">NA</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span>    <span style="color: #BB0000;">NA</span> E      -<span style="color: #BB0000;">101</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span>    <span style="color: #BB0000;">NA</span> F        -<span style="color: #BB0000;">1</span></span>
-<span class="r-in"><span><span class="co"># replace all instances of common na strings</span></span></span>
-<span class="r-in"><span><span class="fu">replace_with_na_all</span><span class="op">(</span><span class="va">dat_ms</span>,</span></span>
-<span class="r-in"><span>                    condition <span class="op">=</span> <span class="op">~</span><span class="va">.x</span> <span class="op"><a href="https://rdrr.io/r/base/match.html" class="external-link">%in%</a></span> <span class="va">common_na_strings</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 5 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>       x y         z</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span>     1 A      -<span style="color: #BB0000;">100</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span>     3 <span style="color: #BB0000;">NA</span>      -<span style="color: #BB0000;">99</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span>    <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span>      -<span style="color: #BB0000;">98</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span>   -<span style="color: #BB0000;">99</span> E      -<span style="color: #BB0000;">101</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span>   -<span style="color: #BB0000;">98</span> F        -<span style="color: #BB0000;">1</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># where works with functions</span></span></span>
-<span class="r-in"><span><span class="fu">replace_with_na_all</span><span class="op">(</span><span class="va">airquality</span>, <span class="op">~</span> <span class="fu"><a href="https://rdrr.io/r/base/MathFun.html" class="external-link">sqrt</a></span><span class="op">(</span><span class="va">.x</span><span class="op">)</span> <span class="op">&lt;</span> <span class="fl">5</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 6</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    Ozone Solar.R  Wind  Temp Month   Day</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>    41     190    <span style="color: #BB0000;">NA</span>    67    <span style="color: #BB0000;">NA</span>    <span style="color: #BB0000;">NA</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>    36     118    <span style="color: #BB0000;">NA</span>    72    <span style="color: #BB0000;">NA</span>    <span style="color: #BB0000;">NA</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>    <span style="color: #BB0000;">NA</span>     149    <span style="color: #BB0000;">NA</span>    74    <span style="color: #BB0000;">NA</span>    <span style="color: #BB0000;">NA</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>    <span style="color: #BB0000;">NA</span>     313    <span style="color: #BB0000;">NA</span>    62    <span style="color: #BB0000;">NA</span>    <span style="color: #BB0000;">NA</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>    <span style="color: #BB0000;">NA</span>      <span style="color: #BB0000;">NA</span>    <span style="color: #BB0000;">NA</span>    56    <span style="color: #BB0000;">NA</span>    <span style="color: #BB0000;">NA</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>    28      <span style="color: #BB0000;">NA</span>    <span style="color: #BB0000;">NA</span>    66    <span style="color: #BB0000;">NA</span>    <span style="color: #BB0000;">NA</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>    <span style="color: #BB0000;">NA</span>     299    <span style="color: #BB0000;">NA</span>    65    <span style="color: #BB0000;">NA</span>    <span style="color: #BB0000;">NA</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>    <span style="color: #BB0000;">NA</span>      99    <span style="color: #BB0000;">NA</span>    59    <span style="color: #BB0000;">NA</span>    <span style="color: #BB0000;">NA</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>    <span style="color: #BB0000;">NA</span>      <span style="color: #BB0000;">NA</span>    <span style="color: #BB0000;">NA</span>    61    <span style="color: #BB0000;">NA</span>    <span style="color: #BB0000;">NA</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>    <span style="color: #BB0000;">NA</span>     194    <span style="color: #BB0000;">NA</span>    69    <span style="color: #BB0000;">NA</span>    <span style="color: #BB0000;">NA</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
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-      <img src="../logo.png" class="logo" alt=""><h1>Replace specified variables with NA where a certain condition is met</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/scoped-replace-with-na.R" class="external-link"><code>R/scoped-replace-with-na.R</code></a></small>
-      <div class="d-none name"><code>replace_with_na_at.Rd</code></div>
-    </div>
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-    <div class="ref-description section level2">
-    <p>Replace specified variables with NA where a certain condition is met</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">replace_with_na_at</span><span class="op">(</span><span class="va">data</span>, <span class="va">.vars</span>, <span class="va">condition</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>dataframe</p></dd>
-
-
-<dt>.vars</dt>
-<dd><p>A character string of variables to replace with NA values</p></dd>
-
-
-<dt>condition</dt>
-<dd><p>A condition required to be TRUE to set NA. Here, the condition
-is specified with a formula, following the syntax: <code>~.x {condition}</code>.
-For example, writing <code>~.x &lt; 20</code> would mean "where a variable value is less
-than 20, replace with NA".</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>a dataframe</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">dat_ms</span> <span class="op">&lt;-</span> <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/tribble.html" class="external-link">tribble</a></span><span class="op">(</span><span class="op">~</span><span class="va">x</span>,  <span class="op">~</span><span class="va">y</span>,    <span class="op">~</span><span class="va">z</span>,</span></span>
-<span class="r-in"><span>                          <span class="fl">1</span>,   <span class="st">"A"</span>,   <span class="op">-</span><span class="fl">100</span>,</span></span>
-<span class="r-in"><span>                          <span class="fl">3</span>,   <span class="st">"N/A"</span>, <span class="op">-</span><span class="fl">99</span>,</span></span>
-<span class="r-in"><span>                          <span class="cn">NA</span>,  <span class="cn">NA</span>,    <span class="op">-</span><span class="fl">98</span>,</span></span>
-<span class="r-in"><span>                          <span class="op">-</span><span class="fl">99</span>, <span class="st">"E"</span>,   <span class="op">-</span><span class="fl">101</span>,</span></span>
-<span class="r-in"><span>                          <span class="op">-</span><span class="fl">98</span>, <span class="st">"F"</span>,   <span class="op">-</span><span class="fl">1</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">dat_ms</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 5 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>       x y         z</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span>     1 A      -<span style="color: #BB0000;">100</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span>     3 N/A     -<span style="color: #BB0000;">99</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span>    <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span>      -<span style="color: #BB0000;">98</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span>   -<span style="color: #BB0000;">99</span> E      -<span style="color: #BB0000;">101</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span>   -<span style="color: #BB0000;">98</span> F        -<span style="color: #BB0000;">1</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">replace_with_na_at</span><span class="op">(</span>data <span class="op">=</span> <span class="va">dat_ms</span>,</span></span>
-<span class="r-in"><span>                 .vars <span class="op">=</span> <span class="st">"x"</span>,</span></span>
-<span class="r-in"><span>                 condition <span class="op">=</span> <span class="op">~</span><span class="va">.x</span> <span class="op">==</span> <span class="op">-</span><span class="fl">99</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 5 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>       x y         z</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span>     1 A      -<span style="color: #BB0000;">100</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span>     3 N/A     -<span style="color: #BB0000;">99</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span>    <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span>      -<span style="color: #BB0000;">98</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span>    <span style="color: #BB0000;">NA</span> E      -<span style="color: #BB0000;">101</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span>   -<span style="color: #BB0000;">98</span> F        -<span style="color: #BB0000;">1</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">replace_with_na_at</span><span class="op">(</span>data <span class="op">=</span> <span class="va">dat_ms</span>,</span></span>
-<span class="r-in"><span>                 .vars <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"x"</span>,<span class="st">"z"</span><span class="op">)</span>,</span></span>
-<span class="r-in"><span>                 condition <span class="op">=</span> <span class="op">~</span><span class="va">.x</span> <span class="op">==</span> <span class="op">-</span><span class="fl">99</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 5 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>       x y         z</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span>     1 A      -<span style="color: #BB0000;">100</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span>     3 N/A      <span style="color: #BB0000;">NA</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span>    <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span>      -<span style="color: #BB0000;">98</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span>    <span style="color: #BB0000;">NA</span> E      -<span style="color: #BB0000;">101</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span>   -<span style="color: #BB0000;">98</span> F        -<span style="color: #BB0000;">1</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># replace using values in common_na_strings</span></span></span>
-<span class="r-in"><span><span class="fu">replace_with_na_at</span><span class="op">(</span>data <span class="op">=</span> <span class="va">dat_ms</span>,</span></span>
-<span class="r-in"><span>                 .vars <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"x"</span>,<span class="st">"z"</span><span class="op">)</span>,</span></span>
-<span class="r-in"><span>                 condition <span class="op">=</span> <span class="op">~</span><span class="va">.x</span> <span class="op"><a href="https://rdrr.io/r/base/match.html" class="external-link">%in%</a></span> <span class="va">common_na_strings</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 5 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>       x y         z</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span>     1 A      -<span style="color: #BB0000;">100</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span>     3 N/A     -<span style="color: #BB0000;">99</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span>    <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span>      -<span style="color: #BB0000;">98</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span>   -<span style="color: #BB0000;">99</span> E      -<span style="color: #BB0000;">101</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span>   -<span style="color: #BB0000;">98</span> F        -<span style="color: #BB0000;">1</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
-
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-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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diff --git a/docs/reference/replace_with_na_if.html b/docs/reference/replace_with_na_if.html
deleted file mode 100644
index 1342ef88..00000000
--- a/docs/reference/replace_with_na_if.html
+++ /dev/null
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-      <img src="../logo.png" class="logo" alt=""><h1>Replace values with NA based on some condition, for variables that meet some predicate</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/scoped-replace-with-na.R" class="external-link"><code>R/scoped-replace-with-na.R</code></a></small>
-      <div class="d-none name"><code>replace_with_na_if.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Replace values with NA based on some condition, for variables that meet some predicate</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">replace_with_na_if</span><span class="op">(</span><span class="va">data</span>, <span class="va">.predicate</span>, <span class="va">condition</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>Dataframe</p></dd>
-
-
-<dt>.predicate</dt>
-<dd><p>A predicate function to be applied to the columns or a
-logical vector.</p></dd>
-
-
-<dt>condition</dt>
-<dd><p>A condition required to be TRUE to set NA. Here, the condition
-is specified with a formula, following the syntax: <code>~.x {condition}</code>.
-For example, writing <code>~.x &lt; 20</code> would mean "where a variable value is less
-than 20, replace with NA".</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>Dataframe</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">dat_ms</span> <span class="op">&lt;-</span> <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/tribble.html" class="external-link">tribble</a></span><span class="op">(</span><span class="op">~</span><span class="va">x</span>,  <span class="op">~</span><span class="va">y</span>,    <span class="op">~</span><span class="va">z</span>,</span></span>
-<span class="r-in"><span>                          <span class="fl">1</span>,   <span class="st">"A"</span>,   <span class="op">-</span><span class="fl">100</span>,</span></span>
-<span class="r-in"><span>                          <span class="fl">3</span>,   <span class="st">"N/A"</span>, <span class="op">-</span><span class="fl">99</span>,</span></span>
-<span class="r-in"><span>                          <span class="cn">NA</span>,  <span class="cn">NA</span>,    <span class="op">-</span><span class="fl">98</span>,</span></span>
-<span class="r-in"><span>                          <span class="op">-</span><span class="fl">99</span>, <span class="st">"E"</span>,   <span class="op">-</span><span class="fl">101</span>,</span></span>
-<span class="r-in"><span>                          <span class="op">-</span><span class="fl">98</span>, <span class="st">"F"</span>,   <span class="op">-</span><span class="fl">1</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">dat_ms</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 5 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>       x y         z</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span>     1 A      -<span style="color: #BB0000;">100</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span>     3 N/A     -<span style="color: #BB0000;">99</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span>    <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span>      -<span style="color: #BB0000;">98</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span>   -<span style="color: #BB0000;">99</span> E      -<span style="color: #BB0000;">101</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span>   -<span style="color: #BB0000;">98</span> F        -<span style="color: #BB0000;">1</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">replace_with_na_if</span><span class="op">(</span>data <span class="op">=</span> <span class="va">dat_ms</span>,</span></span>
-<span class="r-in"><span>                 .predicate <span class="op">=</span> <span class="va">is.character</span>,</span></span>
-<span class="r-in"><span>                 condition <span class="op">=</span> <span class="op">~</span><span class="va">.x</span> <span class="op">==</span> <span class="st">"N/A"</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 5 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>       x y         z</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span>     1 A      -<span style="color: #BB0000;">100</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span>     3 <span style="color: #BB0000;">NA</span>      -<span style="color: #BB0000;">99</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span>    <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span>      -<span style="color: #BB0000;">98</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span>   -<span style="color: #BB0000;">99</span> E      -<span style="color: #BB0000;">101</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span>   -<span style="color: #BB0000;">98</span> F        -<span style="color: #BB0000;">1</span></span>
-<span class="r-in"><span><span class="fu">replace_with_na_if</span><span class="op">(</span>data <span class="op">=</span> <span class="va">dat_ms</span>,</span></span>
-<span class="r-in"><span>                   .predicate <span class="op">=</span> <span class="va">is.character</span>,</span></span>
-<span class="r-in"><span>                   condition <span class="op">=</span> <span class="op">~</span><span class="va">.x</span> <span class="op"><a href="https://rdrr.io/r/base/match.html" class="external-link">%in%</a></span> <span class="va">common_na_strings</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 5 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>       x y         z</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span>     1 A      -<span style="color: #BB0000;">100</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span>     3 <span style="color: #BB0000;">NA</span>      -<span style="color: #BB0000;">99</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span>    <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span>      -<span style="color: #BB0000;">98</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span>   -<span style="color: #BB0000;">99</span> E      -<span style="color: #BB0000;">101</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span>   -<span style="color: #BB0000;">98</span> F        -<span style="color: #BB0000;">1</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu"><a href="replace_with_na.html">replace_with_na</a></span><span class="op">(</span><span class="va">dat_ms</span>,</span></span>
-<span class="r-in"><span>              to_na <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>x <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="op">-</span><span class="fl">99</span>, <span class="op">-</span><span class="fl">98</span><span class="op">)</span>,</span></span>
-<span class="r-in"><span>                           y <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"N/A"</span><span class="op">)</span>,</span></span>
-<span class="r-in"><span>                           z <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="op">-</span><span class="fl">101</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 5 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>       x y         z</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span>     1 A      -<span style="color: #BB0000;">100</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span>     3 N/A     -<span style="color: #BB0000;">99</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span>    <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span>      -<span style="color: #BB0000;">98</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span>   -<span style="color: #BB0000;">99</span> E      -<span style="color: #BB0000;">101</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span>   -<span style="color: #BB0000;">98</span> F        -<span style="color: #BB0000;">1</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
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-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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diff --git a/docs/reference/riskfactors.html b/docs/reference/riskfactors.html
deleted file mode 100644
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-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="The data is a subset of the 2009 survey from BRFSS, an ongoing data
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-Data, 2009. — riskfactors"><meta property="og:description" content="The data is a subset of the 2009 survey from BRFSS, an ongoing data
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-      <img src="../logo.png" class="logo" alt=""><h1>The Behavioral Risk Factor Surveillance System (BRFSS) Survey
-Data, 2009.</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/data-riskfactors.R" class="external-link"><code>R/data-riskfactors.R</code></a></small>
-      <div class="d-none name"><code>riskfactors.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>The data is a subset of the 2009 survey from BRFSS, an ongoing data
-collection program designed to measure behavioral risk factors for the
-adult population (18 years of age or older) living in households.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu"><a href="https://rdrr.io/r/utils/data.html" class="external-link">data</a></span><span class="op">(</span><span class="va">riskfactors</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="format">Format<a class="anchor" aria-label="anchor" href="#format"></a></h2>
-    <p>An object of class <code>tbl_df</code> (inherits from <code>tbl</code>, <code>data.frame</code>) with 245 rows and 34 columns.</p>
-    </div>
-    <div class="section level2">
-    <h2 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a></h2>
-    <p><a href="https://www.cdc.gov/brfss/annual_data/annual_2009.htm" class="external-link">https://www.cdc.gov/brfss/annual_data/annual_2009.htm</a></p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p>the codebook:
-<a href="https://www.cdc.gov/brfss/annual_data/annual_2009.htm" class="external-link">https://www.cdc.gov/brfss/annual_data/annual_2009.htm</a></p>
-<p>Format: a data frame with 245 observations on the following 34
-variables.</p>
-<dl><dt><code>state</code></dt>
-<dd><p>A factor with 52 levels. The labels and states
-corresponding to the labels are as follows: 1:Alabama, 2:Alaska, 4:Arizona,
-5:Arkansas, 6:California,8:Colorado, 9:Connecticut, 10:Delaware, 11:District
-of Columbia,12:Florida, 13:Georgia, 15:Hawaii, 16:Idaho, 1
-:Illinois,18:Indiana, 19:Iowa, 20:Kansas, 21:Kentucky, 22:Louisiana,23:Maine,
-24:Maryland, 25:Massachusetts, 26:Michigan,27:Minnesota, 28:Mississippi,
-2:Missouri, 30:Montana,31:Nebraska, 32:Nevada, 33:New Hampshire, 34:New
-Jersey, 35:NewMexico, 36:New York, 37:North Carolina, 38:North Dakota,
-39:Ohio,40:Oklahoma, 41:Oregon, 42:Pennsylvania, 44:Rhode Island,
-45:SouthCarolina, 46:South Dakota, 47:Tennessee, 48:Texas, 49:Utah,
-50:Vermont, 51:Virginia, 53:Washington, 54:West  Virginia,55:Wisconsin,
-56:Wyoming, 66:Guam, 72:Puerto Rico, 78:Virgin Islands</p></dd>
-
-<dt><code>sex</code></dt>
-<dd><p>A factor with levels <code>Male</code> <code>Female</code>.</p></dd>
-
-<dt><code>age</code></dt>
-<dd><p>A numeric vector from 7 to 97.</p></dd>
-
-<dt><code>weight_lbs</code></dt>
-<dd><p>The weight without shoes in pounds.</p></dd>
-
-<dt><code>height_inch</code></dt>
-<dd><p>The weight without shoes in inches.</p></dd>
-
-<dt><code>bmi</code></dt>
-<dd><p>Body Mass Index (BMI). Computed by weight in Kilogram
-/(height in Meters * height in Meters). Missing if any of weight or
-height is missing.</p></dd>
-
-<dt><code>marital</code></dt>
-<dd><p>A factor with levels <code>Married</code> <code>Divorced</code>
-<code>Widowed</code> <code>Separated</code> <code>NeverMarried</code> <code>UnmarriedCouple</code>.</p></dd>
-
-<dt><code>pregnant</code></dt>
-<dd><p>Whether pregnant now with two levels <code>Yes</code> and
-<code>No</code>.</p></dd>
-
-<dt><code>children</code></dt>
-<dd><p>A numeric vector giving the number of children less
-than 18 years of age in household.</p></dd>
-
-<dt><code>education</code></dt>
-<dd><p>A factor with the education levels <code>1</code>
-<code>2</code> <code>3</code> <code>4</code> <code>5</code> <code>6</code> as 1: Never attended
-school or only kindergarten; 2: Grades 1 through 8 (Elementary);
-3: Grades 9 through 11 (Some high school); 4: Grade 12 or GED
-(High school graduate); 5: College 1 year to 3 years (Some college
-or technical school); 6: College 4 years or more  (College
-graduate).</p></dd>
-
-<dt><code>employment</code></dt>
-<dd><p>A factor showing the employment status with levels
-<code>1</code> <code>2</code> <code>3</code> <code>4</code> <code>5</code> <code>7</code> <code>8</code>. The labels
-mean --  1: Employed for wages; 2: Self-employed; 3: Out of work for more
-than 1 year; 4: Out of work for less that 1 year;  5: A homemaker; 6: A
-student; 7:Retired; 8: Unable to work.</p></dd>
-
-<dt><code>income</code></dt>
-<dd><p>The annual household income from all sources with
-levels <code>&lt;10k</code> <code>10-15k</code> <code>15-20k</code> <code>20-25k</code> <code>25-35k</code>
-<code>35-50k</code> <code>50-75k</code> <code>&gt;75k</code> <code>Dontknow</code> <code>Refused</code>.</p></dd>
-
-<dt><code>veteran</code></dt>
-<dd><p>A factor with levels <code>1</code> <code>2</code> <code>3</code>
-<code>4</code> <code>5</code>. The question for this variable is: Have you ever
-served on active duty in the United States Armed Forces, either in the
-regular military or in a National Guard or military reserve unit? Active
-duty does not include training for the Reserves or National Guard, but
-DOES include activation, for example, for the Persian Gulf War. And the
-labels are meaning: 1: Yes, now on active duty; 2: Yes, on active duty
-during the last 12 months, but not now; 3: Yes, on active duty in the
-past, but not during the last 12 months; 4: No, training for Reserves or
-National Guard only; 5: No, never served in the military.</p></dd>
-
-<dt><code>hispanic</code></dt>
-<dd><p>A factor with levels <code>Yes</code> <code>No</code>
-corresponding to the question: are you Hispanic or Latino?</p></dd>
-
-<dt><code>health_general</code></dt>
-<dd><p>Answer to question "in general your health is"
-with levels  <code>Excellent</code> <code>VeryGood</code> <code>Good</code> <code>Fair</code>
-<code>Poor</code> <code>Refused</code>.</p></dd>
-
-<dt><code>health_physical</code></dt>
-<dd><p>The number of days during the last 30 days
-that the respondent's physical health was not good.  -7 is for "Don't
-know/Not sure", and -9 is for "Refused".</p></dd>
-
-<dt><code>health_mental</code></dt>
-<dd><p>The number of days during the last 30 days
-that the respondent's mental health was not good.  -7 is for
-"Don't know/Not sure", and -9 is for "Refused".</p></dd>
-
-<dt><code>health_poor</code></dt>
-<dd><p>The number of days during the last 30 days
-that poor physical or mental health keep the respondent from doing
-usual activities, such as self-care, work, or recreation. -7 is
-for "Don't know/Not sure", and -9 is for "Refused".</p></dd>
-
-<dt><code>health_cover</code></dt>
-<dd><p>Whether having any kind of health care
-coverage, including health insurance, prepaid plans such as HMOs,
-or government plans such as Medicare. The answer has two levels:
-<code>Yes</code> and <code>No</code>.</p></dd>
-
-<dt><code>provide_care</code></dt>
-<dd><p>Whether providing any such care or assistance
-to a friend or family member during the past month, with levels <code>Yes</code>
-and <code>No</code>.</p></dd>
-
-<dt><code>activity_limited</code></dt>
-<dd><p>Whether being limited in any way in any
-activities because of physical, mental, or emotional problems,
-with levels  <code>Yes</code> and <code>No</code>.</p></dd>
-
-<dt><code>drink_any</code></dt>
-<dd><p>Whether having had at least one drink of
-any alcoholic beverage such as beer, wine, a malt beverage or
-liquor during the past 30 days, with levels <code>Yes</code> and
-<code>No</code>.</p></dd>
-
-<dt><code>drink_days</code></dt>
-<dd><p>The number of days during the past 30 days that
-the respondent had at least one drink of any alcoholic beverage. -7 is
-for "Don't know/Not sure", and -9 is for "Refused".</p></dd>
-
-<dt><code>drink_avg</code></dt>
-<dd><p>The number of drinks on the average the respondent
-had on the days when he/she drank, during the past 30 days. -7 is for
-"Don't know/Not sure", and -9 is for "Refused".</p></dd>
-
-<dt><code>smoke_100</code></dt>
-<dd><p>Whether having smoked at least
-100 cigarettes in the entire life, with levels <code>Yes</code> and
-<code>No</code>.</p></dd>
-
-<dt><code>smoke_days</code></dt>
-<dd><p>The frequency of days now
-smoking, with levels <code>Everyday</code> <code>Somedays</code> and
-<code>NotAtAll</code>(not at all).</p></dd>
-
-<dt><code>smoke_stop</code></dt>
-<dd><p>Whether
-having stopped smoking for  one day or longer during the past 12
-months because the respondent was trying to quit smoking, with
-levels <code>Yes</code> and <code>No</code>.</p></dd>
-
-<dt><code>smoke_last</code></dt>
-<dd><p>A factor
-with levels <code>3</code> <code>4</code> <code>5</code> <code>6</code> <code>7</code> <code>8</code>
-corresponding to the question: how long has it been since last
-smoking cigarettes regularly? The labels mean: 3: Within the past
-6 months (3 months but less than 6 months ago); 4: Within the past
-year (6 months but less than 1 year ago); 5: Within the past 5
-years (1 year but less than 5 years ago); 6: Within the past 10
-years (5 years but less than 10 years ago); 7: 10 years or more;
-8: Never smoked regularly.</p></dd>
-
-<dt><code>diet_fruit</code></dt>
-<dd><p>The number of
-fruit the respondent eat every year, not counting juice. -7 is for
-"Don't know/Not sure", and -9 is for "Refused".</p></dd>
-
-<dt><code>diet_salad</code></dt>
-<dd><p>The number of servings of green   salad the
-respondent eat every year. -7 is for "Don't  know/Not sure",
-and -9 is for "Refused".</p></dd>
-
-<dt><code>diet_potato</code></dt>
-<dd><p>The number of
-servings of potatoes, not including french fries, fried potatoes,
-or potato chips, that the respondent eat every year. -7 is for
-"Don't know/Not sure", and -9 is for "Refused".</p></dd>
-
-<dt><code>diet_carrot</code></dt>
-<dd><p>The number of carrots the respondent eat
-every year. -7 is for  "Don't know/Not sure", and -9 is for
-"Refused".</p></dd>
-
-<dt><code>diet_vegetable</code></dt>
-<dd><p>The number of servings of
-vegetables   the respondent eat every year, not counting carrots,
-potatoes, or salad. -7 is for "Don't know/Not sure", and -9 is
-for "Refused".</p></dd>
-
-<dt><code>diet_juice</code></dt>
-<dd><p>The number of fruit juices
-such as orange, grapefruit, or tomato that the respondent drink
-every year. -7 is   for "Don't know/Not sure", and -9 is for
-"Refused".</p></dd>
-
-
-</dl><p>library(MissingDataGUI) (named brfss)</p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu"><a href="https://docs.ropensci.org/visdat/reference/vis_miss.html" class="external-link">vis_miss</a></span><span class="op">(</span><span class="va">riskfactors</span><span class="op">)</span></span></span>
-<span class="r-plt img"><img src="riskfactors-1.png" alt="" width="700" height="433"></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># Look at the missingness in the variables</span></span></span>
-<span class="r-in"><span><span class="fu"><a href="miss_var_summary.html">miss_var_summary</a></span><span class="op">(</span><span class="va">riskfactors</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 34 × 3</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    variable      n_miss pct_miss</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>          <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> pregnant         215    87.8 </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> smoke_stop       212    86.5 </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> smoke_last       161    65.7 </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> drink_average    135    55.1 </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> drink_days       134    54.7 </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> smoke_days       128    52.2 </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> health_poor      113    46.1 </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> bmi               11     4.49</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> weight_lbs        10     4.08</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> diet_fruit         8     3.27</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 24 more rows</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># and now as a plot</span></span></span>
-<span class="r-in"><span><span class="fu"><a href="gg_miss_var.html">gg_miss_var</a></span><span class="op">(</span><span class="va">riskfactors</span><span class="op">)</span></span></span>
-<span class="r-plt img"><img src="riskfactors-2.png" alt="" width="700" height="433"></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="co"># Look at the missingness in bmi and poor health</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="va">p</span> <span class="op">&lt;-</span></span></span>
-<span class="r-in"><span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">riskfactors</span>,</span></span>
-<span class="r-in"><span>       <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">health_poor</span>,</span></span>
-<span class="r-in"><span>           y <span class="op">=</span> <span class="va">bmi</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span></span>
-<span class="r-in"><span>     <span class="fu"><a href="geom_miss_point.html">geom_miss_point</a></span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span> <span class="va">p</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span> <span class="co"># for each sex?</span></span></span>
-<span class="r-in"><span> <span class="va">p</span> <span class="op">+</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/facet_wrap.html" class="external-link">facet_wrap</a></span><span class="op">(</span><span class="op">~</span><span class="va">sex</span><span class="op">)</span></span></span>
-<span class="r-in"><span> <span class="co"># for each education bracket?</span></span></span>
-<span class="r-in"><span> <span class="va">p</span> <span class="op">+</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/facet_wrap.html" class="external-link">facet_wrap</a></span><span class="op">(</span><span class="op">~</span><span class="va">education</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
-
-
-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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diff --git a/docs/reference/scoped-impute_mean.html b/docs/reference/scoped-impute_mean.html
deleted file mode 100644
index 8b2764b3..00000000
--- a/docs/reference/scoped-impute_mean.html
+++ /dev/null
@@ -1,464 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="impute_mean imputes the mean for a vector. To get it to work on all
-variables, use impute_mean_all. To only impute variables
-that satisfy a specific condition, use the scoped variants,
-impute_below_at, and impute_below_if. To use _at effectively,
-you must know that _at`` affects variables selected with a character vector, or with vars()`."><title>Scoped variants of impute_mean — scoped-impute_mean • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Scoped variants of impute_mean — scoped-impute_mean"><meta property="og:description" content="impute_mean imputes the mean for a vector. To get it to work on all
-variables, use impute_mean_all. To only impute variables
-that satisfy a specific condition, use the scoped variants,
-impute_below_at, and impute_below_if. To use _at effectively,
-you must know that _at`` affects variables selected with a character vector, or with vars()`."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Scoped variants of <code>impute_mean</code></h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/impute_mean.R" class="external-link"><code>R/impute_mean.R</code></a></small>
-      <div class="d-none name"><code>scoped-impute_mean.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p><code>impute_mean</code> imputes the mean for a vector. To get it to work on all
-variables, use <code>impute_mean_all</code>. To only impute variables
-that satisfy a specific condition, use the scoped variants,
-<code>impute_below_at</code>, and <code>impute_below_if</code>. To use <code>_at</code> effectively,
-you must know that <code>_at`` affects variables selected with a character vector, or with </code>vars()`.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">impute_mean_all</span><span class="op">(</span><span class="va">.tbl</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">impute_mean_at</span><span class="op">(</span><span class="va">.tbl</span>, <span class="va">.vars</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">impute_mean_if</span><span class="op">(</span><span class="va">.tbl</span>, <span class="va">.predicate</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>.tbl</dt>
-<dd><p>a data.frame</p></dd>
-
-
-<dt>.vars</dt>
-<dd><p>variables to impute</p></dd>
-
-
-<dt>.predicate</dt>
-<dd><p>variables to impute</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>an dataset with values imputed</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># select variables starting with a particular string.</span></span></span>
-<span class="r-in"><span><span class="fu">impute_mean_all</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>         Ozone  Solar.R Wind Temp Month Day</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 1    41.00000 190.0000  7.4   67     5   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 2    36.00000 118.0000  8.0   72     5   2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 3    12.00000 149.0000 12.6   74     5   3</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 4    18.00000 313.0000 11.5   62     5   4</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 5    42.12931 185.9315 14.3   56     5   5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 6    28.00000 185.9315 14.9   66     5   6</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 7    23.00000 299.0000  8.6   65     5   7</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 8    19.00000  99.0000 13.8   59     5   8</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 9     8.00000  19.0000 20.1   61     5   9</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 10   42.12931 194.0000  8.6   69     5  10</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 11    7.00000 185.9315  6.9   74     5  11</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 12   16.00000 256.0000  9.7   69     5  12</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 13   11.00000 290.0000  9.2   66     5  13</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 14   14.00000 274.0000 10.9   68     5  14</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 15   18.00000  65.0000 13.2   58     5  15</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 16   14.00000 334.0000 11.5   64     5  16</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 17   34.00000 307.0000 12.0   66     5  17</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 18    6.00000  78.0000 18.4   57     5  18</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 19   30.00000 322.0000 11.5   68     5  19</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 20   11.00000  44.0000  9.7   62     5  20</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 21    1.00000   8.0000  9.7   59     5  21</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 22   11.00000 320.0000 16.6   73     5  22</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 23    4.00000  25.0000  9.7   61     5  23</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 24   32.00000  92.0000 12.0   61     5  24</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 25   42.12931  66.0000 16.6   57     5  25</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 26   42.12931 266.0000 14.9   58     5  26</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 27   42.12931 185.9315  8.0   57     5  27</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 28   23.00000  13.0000 12.0   67     5  28</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 29   45.00000 252.0000 14.9   81     5  29</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 30  115.00000 223.0000  5.7   79     5  30</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 31   37.00000 279.0000  7.4   76     5  31</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 32   42.12931 286.0000  8.6   78     6   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 33   42.12931 287.0000  9.7   74     6   2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 34   42.12931 242.0000 16.1   67     6   3</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 35   42.12931 186.0000  9.2   84     6   4</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 36   42.12931 220.0000  8.6   85     6   5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 37   42.12931 264.0000 14.3   79     6   6</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 38   29.00000 127.0000  9.7   82     6   7</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 39   42.12931 273.0000  6.9   87     6   8</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 40   71.00000 291.0000 13.8   90     6   9</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 41   39.00000 323.0000 11.5   87     6  10</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 42   42.12931 259.0000 10.9   93     6  11</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 43   42.12931 250.0000  9.2   92     6  12</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 44   23.00000 148.0000  8.0   82     6  13</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 45   42.12931 332.0000 13.8   80     6  14</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 46   42.12931 322.0000 11.5   79     6  15</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 47   21.00000 191.0000 14.9   77     6  16</span>
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-<span class="r-out co"><span class="r-pr">#&gt;</span> 53   42.12931  59.0000  1.7   76     6  22</span>
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-<span class="r-out co"><span class="r-pr">#&gt;</span> 56   42.12931 135.0000  8.0   75     6  25</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 57   42.12931 127.0000  8.0   78     6  26</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 58   42.12931  47.0000 10.3   73     6  27</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 59   42.12931  98.0000 11.5   80     6  28</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 60   42.12931  31.0000 14.9   77     6  29</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 61   42.12931 138.0000  8.0   83     6  30</span>
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-<span class="r-out co"><span class="r-pr">#&gt;</span> 118  73.00000 215.0000  8.0   86     8  26</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 119  42.12931 153.0000  5.7   88     8  27</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 120  76.00000 203.0000  9.7   97     8  28</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 121 118.00000 225.0000  2.3   94     8  29</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 122  84.00000 237.0000  6.3   96     8  30</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 123  85.00000 188.0000  6.3   94     8  31</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 124  96.00000 167.0000  6.9   91     9   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 125  78.00000 197.0000  5.1   92     9   2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 126  73.00000 183.0000  2.8   93     9   3</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 127  91.00000 189.0000  4.6   93     9   4</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 128  47.00000  95.0000  7.4   87     9   5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 129  32.00000  92.0000 15.5   84     9   6</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 130  20.00000 252.0000 10.9   80     9   7</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 131  23.00000 220.0000 10.3   78     9   8</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 132  21.00000 230.0000 10.9   75     9   9</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 133  24.00000 259.0000  9.7   73     9  10</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 134  44.00000 236.0000 14.9   81     9  11</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 135  21.00000 259.0000 15.5   76     9  12</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 136  28.00000 238.0000  6.3   77     9  13</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 137   9.00000  24.0000 10.9   71     9  14</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 138  13.00000 112.0000 11.5   71     9  15</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 139  46.00000 237.0000  6.9   78     9  16</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 140  18.00000 224.0000 13.8   67     9  17</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 141  13.00000  27.0000 10.3   76     9  18</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 142  24.00000 238.0000 10.3   68     9  19</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 143  16.00000 201.0000  8.0   82     9  20</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 144  13.00000 238.0000 12.6   64     9  21</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 145  23.00000  14.0000  9.2   71     9  22</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 146  36.00000 139.0000 10.3   81     9  23</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 147   7.00000  49.0000 10.3   69     9  24</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 148  14.00000  20.0000 16.6   63     9  25</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 149  30.00000 193.0000  6.9   70     9  26</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 150  42.12931 145.0000 13.2   77     9  27</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 151  14.00000 191.0000 14.3   75     9  28</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 152  18.00000 131.0000  8.0   76     9  29</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 153  20.00000 223.0000 11.5   68     9  30</span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="fu">impute_mean_at</span><span class="op">(</span><span class="va">airquality</span>,</span></span>
-<span class="r-in"><span>                .vars <span class="op">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html" class="external-link">vars</a></span><span class="op">(</span><span class="va">Ozone</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">impute_mean_if</span><span class="op">(</span><span class="va">airquality</span>,</span></span>
-<span class="r-in"><span>                .predicate <span class="op">=</span> <span class="va">is.numeric</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="bind_shadow.html">bind_shadow</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu">impute_mean_all</span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="add_label_shadow.html">add_label_shadow</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Ozone</span>,</span></span>
-<span class="r-in"><span>             y <span class="op">=</span> <span class="va">Solar.R</span>,</span></span>
-<span class="r-in"><span>             colour <span class="op">=</span> <span class="va">any_missing</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span></span>
-<span class="r-in"><span>         <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_point.html" class="external-link">geom_point</a></span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
-
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-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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diff --git a/docs/reference/scoped-impute_median.html b/docs/reference/scoped-impute_median.html
deleted file mode 100644
index ee8142ba..00000000
--- a/docs/reference/scoped-impute_median.html
+++ /dev/null
@@ -1,463 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="impute_median imputes the median for a vector. To get it to work on all
-variables, use impute_median_all. To only impute variables
-that satisfy a specific condition, use the scoped variants,
-impute_below_at, and impute_below_if. To use _at effectively,
-you must know that _at`` affects variables selected with a character vector, or with vars()`."><title>Scoped variants of impute_median — scoped-impute_median • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Scoped variants of impute_median — scoped-impute_median"><meta property="og:description" content="impute_median imputes the median for a vector. To get it to work on all
-variables, use impute_median_all. To only impute variables
-that satisfy a specific condition, use the scoped variants,
-impute_below_at, and impute_below_if. To use _at effectively,
-you must know that _at`` affects variables selected with a character vector, or with vars()`."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Scoped variants of <code>impute_median</code></h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/impute-median.R" class="external-link"><code>R/impute-median.R</code></a></small>
-      <div class="d-none name"><code>scoped-impute_median.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p><code>impute_median</code> imputes the median for a vector. To get it to work on all
-variables, use <code>impute_median_all</code>. To only impute variables
-that satisfy a specific condition, use the scoped variants,
-<code>impute_below_at</code>, and <code>impute_below_if</code>. To use <code>_at</code> effectively,
-you must know that <code>_at`` affects variables selected with a character vector, or with </code>vars()`.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">impute_median_all</span><span class="op">(</span><span class="va">.tbl</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">impute_median_at</span><span class="op">(</span><span class="va">.tbl</span>, <span class="va">.vars</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">impute_median_if</span><span class="op">(</span><span class="va">.tbl</span>, <span class="va">.predicate</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>.tbl</dt>
-<dd><p>a data.frame</p></dd>
-
-
-<dt>.vars</dt>
-<dd><p>variables to impute</p></dd>
-
-
-<dt>.predicate</dt>
-<dd><p>variables to impute</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>an dataset with values imputed</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># select variables starting with a particular string.</span></span></span>
-<span class="r-in"><span><span class="fu">impute_median_all</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>     Ozone Solar.R Wind Temp Month Day</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 1    41.0     190  7.4   67     5   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 2    36.0     118  8.0   72     5   2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 3    12.0     149 12.6   74     5   3</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 4    18.0     313 11.5   62     5   4</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 5    31.5     205 14.3   56     5   5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 6    28.0     205 14.9   66     5   6</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 7    23.0     299  8.6   65     5   7</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 8    19.0      99 13.8   59     5   8</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 9     8.0      19 20.1   61     5   9</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 10   31.5     194  8.6   69     5  10</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 11    7.0     205  6.9   74     5  11</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 12   16.0     256  9.7   69     5  12</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 13   11.0     290  9.2   66     5  13</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 14   14.0     274 10.9   68     5  14</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 15   18.0      65 13.2   58     5  15</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 16   14.0     334 11.5   64     5  16</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 17   34.0     307 12.0   66     5  17</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 18    6.0      78 18.4   57     5  18</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 19   30.0     322 11.5   68     5  19</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 20   11.0      44  9.7   62     5  20</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 21    1.0       8  9.7   59     5  21</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 22   11.0     320 16.6   73     5  22</span>
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-<span class="r-out co"><span class="r-pr">#&gt;</span> 120  76.0     203  9.7   97     8  28</span>
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-<span class="r-out co"><span class="r-pr">#&gt;</span> 127  91.0     189  4.6   93     9   4</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 128  47.0      95  7.4   87     9   5</span>
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-<span class="r-out co"><span class="r-pr">#&gt;</span> 136  28.0     238  6.3   77     9  13</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 137   9.0      24 10.9   71     9  14</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 138  13.0     112 11.5   71     9  15</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 139  46.0     237  6.9   78     9  16</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 140  18.0     224 13.8   67     9  17</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 141  13.0      27 10.3   76     9  18</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 142  24.0     238 10.3   68     9  19</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 143  16.0     201  8.0   82     9  20</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 144  13.0     238 12.6   64     9  21</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 145  23.0      14  9.2   71     9  22</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 146  36.0     139 10.3   81     9  23</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 147   7.0      49 10.3   69     9  24</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 148  14.0      20 16.6   63     9  25</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 149  30.0     193  6.9   70     9  26</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 150  31.5     145 13.2   77     9  27</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 151  14.0     191 14.3   75     9  28</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 152  18.0     131  8.0   76     9  29</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 153  20.0     223 11.5   68     9  30</span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">impute_median_at</span><span class="op">(</span><span class="va">airquality</span>,</span></span>
-<span class="r-in"><span>               .vars <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Ozone"</span>, <span class="st">"Solar.R"</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>     Ozone Solar.R Wind Temp Month Day</span>
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-<span class="r-out co"><span class="r-pr">#&gt;</span> 5    31.5     205 14.3   56     5   5</span>
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-<span class="r-out co"><span class="r-pr">#&gt;</span> 8    19.0      99 13.8   59     5   8</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 9     8.0      19 20.1   61     5   9</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 10   31.5     194  8.6   69     5  10</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 11    7.0     205  6.9   74     5  11</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 12   16.0     256  9.7   69     5  12</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 13   11.0     290  9.2   66     5  13</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 14   14.0     274 10.9   68     5  14</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 15   18.0      65 13.2   58     5  15</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 16   14.0     334 11.5   64     5  16</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 17   34.0     307 12.0   66     5  17</span>
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-<span class="r-out co"><span class="r-pr">#&gt;</span> 20   11.0      44  9.7   62     5  20</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 21    1.0       8  9.7   59     5  21</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 22   11.0     320 16.6   73     5  22</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 23    4.0      25  9.7   61     5  23</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 24   32.0      92 12.0   61     5  24</span>
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-<span class="r-out co"><span class="r-pr">#&gt;</span> 28   23.0      13 12.0   67     5  28</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 29   45.0     252 14.9   81     5  29</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 30  115.0     223  5.7   79     5  30</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 31   37.0     279  7.4   76     5  31</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 32   31.5     286  8.6   78     6   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 33   31.5     287  9.7   74     6   2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 34   31.5     242 16.1   67     6   3</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 35   31.5     186  9.2   84     6   4</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 36   31.5     220  8.6   85     6   5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 37   31.5     264 14.3   79     6   6</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 38   29.0     127  9.7   82     6   7</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 39   31.5     273  6.9   87     6   8</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 40   71.0     291 13.8   90     6   9</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 41   39.0     323 11.5   87     6  10</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 42   31.5     259 10.9   93     6  11</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 43   31.5     250  9.2   92     6  12</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 44   23.0     148  8.0   82     6  13</span>
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-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="fu">impute_median_at</span><span class="op">(</span><span class="va">airquality</span>,</span></span>
-<span class="r-in"><span>                .vars <span class="op">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html" class="external-link">vars</a></span><span class="op">(</span><span class="va">Ozone</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">impute_median_if</span><span class="op">(</span><span class="va">airquality</span>,</span></span>
-<span class="r-in"><span>                .predicate <span class="op">=</span> <span class="va">is.numeric</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="bind_shadow.html">bind_shadow</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu">impute_median_all</span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="add_label_shadow.html">add_label_shadow</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">Ozone</span>,</span></span>
-<span class="r-in"><span>             y <span class="op">=</span> <span class="va">Solar.R</span>,</span></span>
-<span class="r-in"><span>             colour <span class="op">=</span> <span class="va">any_missing</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span></span>
-<span class="r-in"><span>         <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_point.html" class="external-link">geom_point</a></span><span class="op">(</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
-
-
-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
-</div>
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-<div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
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diff --git a/docs/reference/shade.html b/docs/reference/shade.html
deleted file mode 100644
index d735c595..00000000
--- a/docs/reference/shade.html
+++ /dev/null
@@ -1,133 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Returns (at least) factors of !NA and NA, where !NA indicates a datum that is
-not missing, and NA indicates missingness. It also allows you to specify
-some new missings, if you like. This function is what powers the factor
-levels in as_shadow()."><title>Create new levels of missing — shade • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Create new levels of missing — shade"><meta property="og:description" content="Returns (at least) factors of !NA and NA, where !NA indicates a datum that is
-not missing, and NA indicates missingness. It also allows you to specify
-some new missings, if you like. This function is what powers the factor
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-      <div class="d-none name"><code>shade.Rd</code></div>
-    </div>
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-    <p>Returns (at least) factors of !NA and NA, where !NA indicates a datum that is
-not missing, and NA indicates missingness. It also allows you to specify
-some new missings, if you like. This function is what powers the factor
-levels in <code><a href="as_shadow.html">as_shadow()</a></code>.</p>
-    </div>
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-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">shade</span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span>, extra_levels <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
-<dd><p>a vector</p></dd>
-
-
-<dt>...</dt>
-<dd><p>additional levels of missing to add</p></dd>
-
-
-<dt>extra_levels</dt>
-<dd><p>extra levels you might to specify for the factor.</p></dd>
-
-</dl></div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">df</span> <span class="op">&lt;-</span> <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/tribble.html" class="external-link">tribble</a></span><span class="op">(</span></span></span>
-<span class="r-in"><span>  <span class="op">~</span><span class="va">wind</span>, <span class="op">~</span><span class="va">temp</span>,</span></span>
-<span class="r-in"><span>  <span class="op">-</span><span class="fl">99</span>,    <span class="fl">45</span>,</span></span>
-<span class="r-in"><span>  <span class="fl">68</span>,    <span class="cn">NA</span>,</span></span>
-<span class="r-in"><span>  <span class="fl">72</span>,    <span class="fl">25</span></span></span>
-<span class="r-in"><span>  <span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">shade</span><span class="op">(</span><span class="va">df</span><span class="op">$</span><span class="va">wind</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] !NA !NA !NA</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> Levels: !NA NA</span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">shade</span><span class="op">(</span><span class="va">df</span><span class="op">$</span><span class="va">wind</span>, inst_fail <span class="op">=</span> <span class="op">-</span><span class="fl">99</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] NA_inst_fail !NA          !NA         </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> Levels: !NA NA NA_inst_fail</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/shadow_expand_relevel.html b/docs/reference/shadow_expand_relevel.html
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-    <small class="dont-index">Source: <a href='https://github.com/njtierney/naniar/blob/master/R/shadow-recode.R'><code>R/shadow-recode.R</code></a></small>
-    <div class="hidden name"><code>shadow_expand_relevel.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Internal function to handle appropriate expansion and releveling of
-shadow variables.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>shadow_expand_relevel</span>(<span class='no'>.var</span>, <span class='no'>suffix</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>.var</th>
-      <td><p>a variable in a data.frame</p></td>
-    </tr>
-    <tr>
-      <th>suffix</th>
-      <td><p>a character suffix to add to NA_, e.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>a factor with expanded levels</p>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='kw'>if</span> (<span class='fl'>FALSE</span>) {
-<span class='no'>df</span> <span class='kw'>&lt;-</span> <span class='kw pkg'>tibble</span><span class='kw ns'>::</span><span class='fu'><a href='https://tibble.tidyverse.org/reference/tribble.html'>tribble</a></span>(
-  ~<span class='no'>wind</span>, ~<span class='no'>temp</span>,
-  -<span class='fl'>99</span>,    <span class='fl'>45</span>,
-  <span class='fl'>68</span>,    <span class='fl'>NA</span>,
-  <span class='fl'>72</span>,    <span class='fl'>25</span>
-)
-
-<span class='no'>dfs</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='bind_shadow.html'>bind_shadow</a></span>(<span class='no'>df</span>)
-
-<span class='no'>test_shade</span> <span class='kw'>&lt;-</span> <span class='no'>dfs</span>$<span class='no'>wind_NA</span>
-
-<span class='fu'>shadow_expand_relevel</span>(<span class='no'>test_shade</span>, <span class='st'>"weee"</span>)
-
-<span class='no'>dfs</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'>mutate</span>(<span class='kw'>temp_NA</span> <span class='kw'>=</span> <span class='fu'>shadow_expand_relevel</span>(<span class='no'>temp_NA</span>, <span class='st'>"weee"</span>))
-
-
-<span class='co'># test that this breaks</span>
-<span class='fu'>shadow_expand_relevel</span>(<span class='no'>airquality</span>, <span class='st'>"weee"</span>)
-}</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
-      <li><a href="#arguments">Arguments</a></li>
-      <li><a href="#value">Value</a></li>
-      <li><a href="#examples">Examples</a></li>
-    </ul>
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diff --git a/docs/reference/shadow_long.html b/docs/reference/shadow_long.html
deleted file mode 100644
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--- a/docs/reference/shadow_long.html
+++ /dev/null
@@ -1,171 +0,0 @@
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-      <img src="../logo.png" class="logo" alt=""><h1>Reshape shadow data into a long format</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/shadows.R" class="external-link"><code>R/shadows.R</code></a></small>
-      <div class="d-none name"><code>shadow_long.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Once data is in <code>nabular</code> form, where the shadow is bound to the data, it
-can be useful to reshape it into a long format with the columns</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">shadow_long</span><span class="op">(</span><span class="va">shadow_data</span>, <span class="va">...</span>, only_main_vars <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>shadow_data</dt>
-<dd><p>a data.frame</p></dd>
-
-
-<dt>...</dt>
-<dd><p>bare name of variables that you want to focus on</p></dd>
-
-
-<dt>only_main_vars</dt>
-<dd><p>logical - do you want to filter down to main variables?</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>data in long format, with columns <code>variable</code>, <code>value</code>, <code>variable_NA</code>, and <code>value_NA</code>.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">aq_shadow</span> <span class="op">&lt;-</span> <span class="fu"><a href="bind_shadow.html">bind_shadow</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">shadow_long</span><span class="op">(</span><span class="va">aq_shadow</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 918 × 4</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    variable value variable_NA value_NA</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>       <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> Ozone     41   Ozone_NA    !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> Solar.R  190   Solar.R_NA  !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> Wind       7.4 Wind_NA     !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> Temp      67   Temp_NA     !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> Month      5   Month_NA    !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> Day        1   Day_NA      !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> Ozone     36   Ozone_NA    !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> Solar.R  118   Solar.R_NA  !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> Wind       8   Wind_NA     !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> Temp      72   Temp_NA     !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 908 more rows</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># then filter only on Ozone</span></span></span>
-<span class="r-in"><span><span class="fu">shadow_long</span><span class="op">(</span><span class="va">aq_shadow</span>, <span class="va">Ozone</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 4</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    variable value variable_NA value_NA</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>       <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> Ozone       41 Ozone_NA    !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> Ozone       36 Ozone_NA    !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> Ozone       12 Ozone_NA    !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> Ozone       18 Ozone_NA    !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> Ozone       <span style="color: #BB0000;">NA</span> Ozone_NA    NA      </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> Ozone       28 Ozone_NA    !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> Ozone       23 Ozone_NA    !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> Ozone       19 Ozone_NA    !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> Ozone        8 Ozone_NA    !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> Ozone       <span style="color: #BB0000;">NA</span> Ozone_NA    NA      </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">shadow_long</span><span class="op">(</span><span class="va">aq_shadow</span>, <span class="va">Ozone</span>, <span class="va">Solar.R</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 306 × 4</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    variable value variable_NA value_NA</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>       <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> Ozone       41 Ozone_NA    !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> Solar.R    190 Solar.R_NA  !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> Ozone       36 Ozone_NA    !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> Solar.R    118 Solar.R_NA  !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> Ozone       12 Ozone_NA    !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> Solar.R    149 Solar.R_NA  !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> Ozone       18 Ozone_NA    !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> Solar.R    313 Solar.R_NA  !NA     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> Ozone       <span style="color: #BB0000;">NA</span> Ozone_NA    NA      </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> Solar.R     <span style="color: #BB0000;">NA</span> Solar.R_NA  NA      </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 296 more rows</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
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-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
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diff --git a/docs/reference/shadow_shift.html b/docs/reference/shadow_shift.html
deleted file mode 100644
index f37f7f66..00000000
--- a/docs/reference/shadow_shift.html
+++ /dev/null
@@ -1,159 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="shadow_shift transforms missing values to facilitate visualisation, and has
-different behaviour for different types of variables. For numeric
-variables, the values are shifted to 10% below the minimum value for a given
-variable plus some jittered noise, to separate repeated values, so that
-missing values can be visualised along with the rest of the data."><title>Shift missing values to facilitate missing data exploration/visualisation — shadow_shift • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Shift missing values to facilitate missing data exploration/visualisation — shadow_shift"><meta property="og:description" content="shadow_shift transforms missing values to facilitate visualisation, and has
-different behaviour for different types of variables. For numeric
-variables, the values are shifted to 10% below the minimum value for a given
-variable plus some jittered noise, to separate repeated values, so that
-missing values can be visualised along with the rest of the data."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-<div class="row">
-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Shift missing values to facilitate missing data exploration/visualisation</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/shadow-shifters.R" class="external-link"><code>R/shadow-shifters.R</code></a></small>
-      <div class="d-none name"><code>shadow_shift.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p><code>shadow_shift</code> transforms missing values to facilitate visualisation, and has
-different behaviour for different types of variables. For numeric
-variables, the values are shifted to 10% below the minimum value for a given
-variable plus some jittered noise, to separate repeated values, so that
-missing values can be visualised along with the rest of the data.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">shadow_shift</span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
-<dd><p>a variable of interest to shift</p></dd>
-
-
-<dt>...</dt>
-<dd><p>extra arguments to pass</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="add_shadow_shift.html">add_shadow_shift()</a></code> <code><a href="cast_shadow_shift.html">cast_shadow_shift()</a></code> <code><a href="cast_shadow_shift_label.html">cast_shadow_shift_label()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">airquality</span><span class="op">$</span><span class="va">Ozone</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   [1]  41  36  12  18  NA  28  23  19   8  NA   7  16  11  14  18  14  34   6</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [19]  30  11   1  11   4  32  NA  NA  NA  23  45 115  37  NA  NA  NA  NA  NA</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [37]  NA  29  NA  71  39  NA  NA  23  NA  NA  21  37  20  12  13  NA  NA  NA</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [55]  NA  NA  NA  NA  NA  NA  NA 135  49  32  NA  64  40  77  97  97  85  NA</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [73]  10  27  NA   7  48  35  61  79  63  16  NA  NA  80 108  20  52  82  50</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [91]  64  59  39   9  16  78  35  66 122  89 110  NA  NA  44  28  65  NA  22</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [109]  59  23  31  44  21   9  NA  45 168  73  NA  76 118  84  85  96  78  73</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [127]  91  47  32  20  23  21  24  44  21  28   9  13  46  18  13  24  16  13</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [145]  23  36   7  14  30  NA  14  18  20</span>
-<span class="r-in"><span><span class="fu">shadow_shift</span><span class="op">(</span><span class="va">airquality</span><span class="op">$</span><span class="va">Ozone</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   [1]  41.00000  36.00000  12.00000  18.00000 -19.72321  28.00000  23.00000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   [8]  19.00000   8.00000 -18.51277   7.00000  16.00000  11.00000  14.00000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [15]  18.00000  14.00000  34.00000   6.00000  30.00000  11.00000   1.00000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [22]  11.00000   4.00000  32.00000 -17.81863 -19.43853 -15.14310  23.00000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [29]  45.00000 115.00000  37.00000 -16.17315 -14.65883 -17.85609 -13.29299</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [36] -16.16323 -19.60935  29.00000 -19.65780  71.00000  39.00000 -13.40961</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [43] -13.53728  23.00000 -19.65993 -16.48342  21.00000  37.00000  20.00000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [50]  12.00000  13.00000 -17.17718 -16.74073 -13.65786 -16.78786 -12.30098</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [57] -13.33171 -16.77414 -17.08225 -15.98818 -19.17558 135.00000  49.00000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [64]  32.00000 -14.27138  64.00000  40.00000  77.00000  97.00000  97.00000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [71]  85.00000 -13.51764  10.00000  27.00000 -13.48998   7.00000  48.00000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [78]  35.00000  61.00000  79.00000  63.00000  16.00000 -16.92150 -16.60335</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [85]  80.00000 108.00000  20.00000  52.00000  82.00000  50.00000  64.00000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [92]  59.00000  39.00000   9.00000  16.00000  78.00000  35.00000  66.00000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [99] 122.00000  89.00000 110.00000 -14.78907 -16.19151  44.00000  28.00000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [106]  65.00000 -19.73591  22.00000  59.00000  23.00000  31.00000  44.00000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [113]  21.00000   9.00000 -18.92235  45.00000 168.00000  73.00000 -14.86296</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [120]  76.00000 118.00000  84.00000  85.00000  96.00000  78.00000  73.00000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [127]  91.00000  47.00000  32.00000  20.00000  23.00000  21.00000  24.00000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [134]  44.00000  21.00000  28.00000   9.00000  13.00000  46.00000  18.00000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [141]  13.00000  24.00000  16.00000  13.00000  23.00000  36.00000   7.00000</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [148]  14.00000  30.00000 -14.83089  14.00000  18.00000  20.00000</span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="va">airquality</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
-<span class="r-in"><span>    <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>Ozone_shift <span class="op">=</span> <span class="fu">shadow_shift</span><span class="op">(</span><span class="va">Ozone</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
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diff --git a/docs/reference/shadow_shift.numeric.html b/docs/reference/shadow_shift.numeric.html
deleted file mode 100644
index b03857aa..00000000
--- a/docs/reference/shadow_shift.numeric.html
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-      <img src="../logo.png" class="logo" alt=""><h1>Shift (impute) numeric values for graphical exploration</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/shadow-shifters.R" class="external-link"><code>R/shadow-shifters.R</code></a></small>
-      <div class="d-none name"><code>shadow_shift.numeric.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Shift (impute) numeric values for graphical exploration</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># S3 method for numeric</span></span>
-<span><span class="fu"><a href="shadow_shift.html">shadow_shift</a></span><span class="op">(</span></span>
-<span>  <span class="va">x</span>,</span>
-<span>  prop_below <span class="op">=</span> <span class="fl">0.1</span>,</span>
-<span>  jitter <span class="op">=</span> <span class="fl">0.05</span>,</span>
-<span>  seed_shift <span class="op">=</span> <span class="fl">2017</span> <span class="op">-</span> <span class="fl">7</span> <span class="op">-</span> <span class="fl">1</span> <span class="op">-</span> <span class="fl">1850</span>,</span>
-<span>  <span class="va">...</span></span>
-<span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
-<dd><p>a variable of interest to shift</p></dd>
-
-
-<dt>prop_below</dt>
-<dd><p>the degree to shift the values. default is</p></dd>
-
-
-<dt>jitter</dt>
-<dd><p>the amount of jitter to add. default is 0.05</p></dd>
-
-
-<dt>seed_shift</dt>
-<dd><p>a random seed to set, if you like</p></dd>
-
-
-<dt>...</dt>
-<dd><p>extra arguments to pass</p></dd>
-
-</dl></div>
-
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diff --git a/docs/reference/stat_miss_point.html b/docs/reference/stat_miss_point.html
deleted file mode 100644
index d249d851..00000000
--- a/docs/reference/stat_miss_point.html
+++ /dev/null
@@ -1,166 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="stat_miss_point adds a geometry for displaying missingness to
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-<div class="row">
-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>stat_miss_point</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/stat-miss-point.R" class="external-link"><code>R/stat-miss-point.R</code></a></small>
-      <div class="d-none name"><code>stat_miss_point.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>stat_miss_point adds a geometry for displaying missingness to
-geom_point</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">stat_miss_point</span><span class="op">(</span></span>
-<span>  mapping <span class="op">=</span> <span class="cn">NULL</span>,</span>
-<span>  data <span class="op">=</span> <span class="cn">NULL</span>,</span>
-<span>  prop_below <span class="op">=</span> <span class="fl">0.1</span>,</span>
-<span>  jitter <span class="op">=</span> <span class="fl">0.05</span>,</span>
-<span>  geom <span class="op">=</span> <span class="st">"point"</span>,</span>
-<span>  position <span class="op">=</span> <span class="st">"identity"</span>,</span>
-<span>  na.rm <span class="op">=</span> <span class="cn">FALSE</span>,</span>
-<span>  show.legend <span class="op">=</span> <span class="cn">NA</span>,</span>
-<span>  inherit.aes <span class="op">=</span> <span class="cn">TRUE</span>,</span>
-<span>  <span class="va">...</span></span>
-<span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>mapping</dt>
-<dd><p>Set of aesthetic mappings created by <code><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">ggplot2::aes()</a></code>
-or <code><a href="https://ggplot2.tidyverse.org/reference/aes_.html" class="external-link">ggplot2::aes_()</a></code>. If specified and <code>inherit.aes = TRUE</code>
-(the default), is combined with the default mapping at the top level of the
-plot. You only need to supply mapping if there isn't a mapping defined for
-the plot.</p></dd>
-
-
-<dt>data</dt>
-<dd><p>A data frame. If specified, overrides the default data frame
-defined at the top level of the plot.</p></dd>
-
-
-<dt>prop_below</dt>
-<dd><p>the degree to shift the values. The default is 0.1</p></dd>
-
-
-<dt>jitter</dt>
-<dd><p>the amount of jitter to add. The default is 0.05</p></dd>
-
-
-<dt>geom, </dt>
-<dd><p>stat Override the default connection between <code>geom_point</code> and
-<code>stat_point</code>.</p></dd>
-
-
-<dt>position</dt>
-<dd><p>Position adjustment, either as a string, or the result of a
-call to a position adjustment function</p></dd>
-
-
-<dt>na.rm</dt>
-<dd><p>If <code>FALSE</code> (the default), removes missing values with a warning.
-If <code>TRUE</code> silently removes missing values.</p></dd>
-
-
-<dt>show.legend</dt>
-<dd><p>logical. Should this layer be included in the legends?
-<code>NA</code>, the default, includes if any aesthetics are mapped. <code>FALSE</code>
-never includes, and <code>TRUE</code> always includes.</p></dd>
-
-
-<dt>inherit.aes</dt>
-<dd><p>If <code>FALSE</code>, overrides the default aesthetics, rather
-than combining with them. This is most useful for helper functions that
-define both data and aesthetics and shouldn't inherit behaviour from the
-default plot specification, e.g. borders.</p></dd>
-
-
-<dt>...</dt>
-<dd><p>other arguments passed on to <code><a href="https://ggplot2.tidyverse.org/reference/layer.html" class="external-link">ggplot2::layer()</a></code>. There
-are three types of arguments you can use here:</p><ul><li><p>Aesthetics: to set an aesthetic to a fixed value, like
-<code>color = "red"</code> or <code>size = 3.</code></p></li>
-<li><p>Other arguments to the layer, for example you override the default
-<code>stat</code> associated with the layer.</p></li>
-<li><p>Other arguments passed on to the stat.</p></li>
-</ul></dd>
-
-</dl></div>
-
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
-
-
-    <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Nicholas Tierney, <a href="http://www.dicook.org/" class="external-link">Di Cook</a>, <a href="https://milesmcbain.xyz/" class="external-link">Miles McBain</a>, <a href="https://colinfay.me/" class="external-link">Colin Fay</a>.</p>
-</div>
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diff --git a/docs/reference/stat_missing_point.html b/docs/reference/stat_missing_point.html
deleted file mode 100644
index 833deb88..00000000
--- a/docs/reference/stat_missing_point.html
+++ /dev/null
@@ -1,182 +0,0 @@
-<!-- Generated by pkgdown: do not edit by hand -->
-<!DOCTYPE html>
-<html>
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-<meta http-equiv="X-UA-Compatible" content="IE=edge">
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-    <div class="page-header">
-    <h1>stat_missing_point</h1>
-    </div>
-
-    
-    <p>stat_missing_point adds a geometry for displaying missingness to geom_point</p>
-    
-
-    <pre class="usage"><span class='fu'>stat_missing_point</span>(<span class='kw'>mapping</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>data</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>geom</span> <span class='kw'>=</span> <span class='st'>"point"</span>,
-  <span class='kw'>position</span> <span class='kw'>=</span> <span class='st'>"identity"</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='kw'>show.legend</span> <span class='kw'>=</span> <span class='fl'>NA</span>,
-  <span class='kw'>inherit.aes</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='no'>...</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a> Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>mapping</th>
-      <td><p>Set of aesthetic mappings created by <code><a href='http://www.rdocumentation.org/packages/ggplot2/topics/aes'>aes</a></code>
-or <code><a href='http://www.rdocumentation.org/packages/ggplot2/topics/aes_'>aes_</a></code>. If specified and <code>inherit.aes = TRUE</code>
-(the default), is combined with the default mapping at the top level of the
-plot. You only need to supply mapping if there isn't a mapping defined for
-the plot.</p></td>
-    </tr>
-    <tr>
-      <th>data</th>
-      <td><p>A data frame. If specified, overrides the default data frame
-defined at the top level of the plot.</p></td>
-    </tr>
-    <tr>
-      <th>geom, </th>
-      <td><p>stat Override the default connection between <code>geom_point</code> and <code>stat_point</code>.</p></td>
-    </tr>
-    <tr>
-      <th>position</th>
-      <td><p>Position adjustment, either as a string, or the result of a
-call to a position adjustment function</p></td>
-    </tr>
-    <tr>
-      <th>na.rm</th>
-      <td><p>If <code>FALSE</code> (the default), removes missing values with a
-warning. If <code>TRUE</code> silently removes missing values.</p></td>
-    </tr>
-    <tr>
-      <th>show.legend</th>
-      <td><p>logical. Should this layer be included in the legends?
-<code>NA</code>, the default, includes if any aesthetics are mapped. <code>FALSE</code>
-never includes, and <code>TRUE</code> always includes.</p></td>
-    </tr>
-    <tr>
-      <th>inherit.aes</th>
-      <td><p>If <code>FALSE</code>, overrides the default aesthetics, rather
-than combining with them. This is most useful for helper functions that
-define both data and aesthetics and shouldn't inherit behaviour from the
-default plot specification, e.g. borders.</p></td>
-    </tr>
-    <tr>
-      <th>...</th>
-      <td><p>other arguments passed on to <code><a href='http://www.rdocumentation.org/packages/ggplot2/topics/layer'>layer</a></code>. There
-are three types of arguments you can use here:</p><ul>
-<li><p>Aesthetics: to set an aesthetic to a fixed value, like
- <code>color = "red"</code> or <code>size = 3.</code></p></li>
-<li><p>Other arguments to the layer, for example you override the default
- <code>stat</code> associated with the layer.</p></li>
-<li><p>Other arguments passed on to the stat.</p></li>
-</ul></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="note"><a class="anchor" href="#note"></a>Note</h2>
-
-    <p>Very first attempt at creating a geom that is compatible with ggplot2.
-Data plotting works. Still todo:
-Warning message if na.rm = T is supplied.</p>
-    
-
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
-      <li><a href="#arguments">Arguments</a></li>
-      
-      <li><a href="#note">Note</a></li>
-          </ul>
-
-  </div>
-</div>
-
-      <footer>
-      <div class="copyright">
-  <p>Developed by Nicholas Tierney, Di Cook, Miles McBain.</p>
-</div>
-
-<div class="pkgdown">
-  <p>Site built with <a href="http://hadley.github.io/pkgdown/">pkgdown</a>.</p>
-</div>
-
-      </footer>
-   </div>
-
-  </body>
-</html>
diff --git a/docs/reference/summarise_missingness.html b/docs/reference/summarise_missingness.html
deleted file mode 100644
index 47bdf889..00000000
--- a/docs/reference/summarise_missingness.html
+++ /dev/null
@@ -1,131 +0,0 @@
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-<!DOCTYPE html>
-<html>
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-<meta http-equiv="X-UA-Compatible" content="IE=edge">
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-<title>Collate summary measures from narnia into one tibble — summarise_missingness • narnia</title>
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-
-      
-      </header>
-
-      <div class="row">
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-    <div class="page-header">
-    <h1>Collate summary measures from narnia into one tibble</h1>
-    </div>
-
-    
-    <p>Deprecated as of version 0.0.6.9000. Please use miss_summary instead.</p>
-    
-
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-    
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <p>miss_summary</p>
-    
-
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
-      <li><a href="#arguments">Arguments</a></li>
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diff --git a/docs/reference/summary_missing_case.html b/docs/reference/summary_missing_case.html
deleted file mode 100644
index 0efa86b5..00000000
--- a/docs/reference/summary_missing_case.html
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-      </header>
-
-      <div class="row">
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-    <div class="page-header">
-    <h1>Summarise the missingness in each case</h1>
-    </div>
-
-    
-    <p>Deprecated as of version 0.0.6.9000. Please use miss_case_summary instead.</p>
-    
-
-    <pre class="usage"><span class='fu'>summary_missing_case</span>(<span class='no'>...</span>)</pre>
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-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <p>miss_case_summary</p>
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-
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-  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
-    <h2>Contents</h2>
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diff --git a/docs/reference/summary_missing_var.html b/docs/reference/summary_missing_var.html
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-
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-      </header>
-
-      <div class="row">
-  <div class="col-md-9 contents">
-    <div class="page-header">
-    <h1>Summarise the missingness in each variable</h1>
-    </div>
-
-    
-    <p>Deprecated as of version 0.0.6.9000. Please use miss_var_summary instead.</p>
-    
-
-    <pre class="usage"><span class='fu'>summary_missing_var</span>(<span class='no'>...</span>)</pre>
-    
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-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>...</th>
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-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <p>miss_var_summary</p>
-    
-
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
-      <li><a href="#arguments">Arguments</a></li>
-      
-      <li><a href="#see-also">See also</a></li>
-          </ul>
-
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-</div>
-
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diff --git a/docs/reference/table_missing_case.html b/docs/reference/table_missing_case.html
deleted file mode 100644
index d1072d47..00000000
--- a/docs/reference/table_missing_case.html
+++ /dev/null
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-      </header>
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-    <div class="page-header">
-    <h1>Tabulate missings in cases.</h1>
-    </div>
-
-    
-    <p>Deprecated as of version 0.0.6.9000. Please use miss_case_table instead.</p>
-    
-
-    <pre class="usage"><span class='fu'>table_missing_case</span>(<span class='no'>...</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a> Arguments</h2>
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-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>...</th>
-      <td><p>so that users can still receive meaningful error</p></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <p>miss_case_table</p>
-    
-
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
-      <li><a href="#arguments">Arguments</a></li>
-      
-      <li><a href="#see-also">See also</a></li>
-          </ul>
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diff --git a/docs/reference/table_missing_var.html b/docs/reference/table_missing_var.html
deleted file mode 100644
index d43d8908..00000000
--- a/docs/reference/table_missing_var.html
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-    <div class="page-header">
-    <h1>Tabulate the missings in the variables</h1>
-    </div>
-
-    
-    <p>Deprecated as of version 0.0.6.9000. Please use miss_var_table instead.</p>
-    
-
-    <pre class="usage"><span class='fu'>table_missing_var</span>(<span class='no'>...</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a> Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>...</th>
-      <td><p>so that users can still receive meaningful error</p></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <p>miss_var_table</p>
-    
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-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
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diff --git a/docs/reference/tao.html b/docs/reference/tao.html
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-    <h1>West Pacific Tropical Atmosphere Ocean Data, 1993 &amp; 1997.</h1>
-    </div>
-
-    
-    <p>Real-time data from moored ocean buoys for improved detection,
-understanding and prediction of El Ni'o and La Ni'a.</p>
-    
-
-    <pre class="usage"><span class='fu'>data</span>(<span class='no'>tao</span>)</pre>
-        
-    <h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
-
-    <p><a href='http://www.pmel.noaa.gov/tao/data_deliv/deliv.html'>http://www.pmel.noaa.gov/tao/data_deliv/deliv.html</a></p>
-    
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>The data is collected by the Tropical Atmosphere Ocean project (
-<a href='http://www.pmel.noaa.gov/tao/index.shtml'>http://www.pmel.noaa.gov/tao/index.shtml</a>).</p>
-<p>Format: a data frame with 736 observations on the following 8
-variables.</p><dl class='dl-horizontal'>
- <dt><code>latitude</code></dt><dd><p>A factor with
-levels <code>-5</code>  <code>-2</code> <code>0</code>.</p></dd> <dt><code>longitude</code></dt><dd><p>A
-factor with levels <code>-110</code> <code>-95</code>.</p></dd>
-<dt><code>sea.surface.temp</code></dt><dd><p>Sea surface temperature(degree
-Celsius), measured by the TAO buoys at one meter below the
-surface.</p></dd>  <dt><code>air.temp</code></dt><dd><p>Air temperature(degree Celsius),
-measured by the TAO buoys three meters above the sea surface.</p></dd>
-<dt><code>humidity</code></dt><dd><p>Relative humidity(<!-- %), measured by the TAO -->
-buoys 3 meters above the sea surface.</p></dd> <dt><code>uwind</code></dt><dd><p>The
-East-West wind vector components(M/s).  TAO buoys measure the wind
-speed and direction four meters above the sea surface. If it is
-positive, the East-West component of the wind is blowing towards
-the East. If it is negative, this component is blowing towards the
-West.</p></dd><dt><code>vwind</code></dt><dd><p>The North-South wind vector
-components(M/s). TAO buoys measure the wind speed and direction
-four meters above the sea surface. If it is positive, the
-North-South component of the wind is blowing towards the North.
-If it is negative, this component is blowing towards the South.</p></dd></dl>
-    
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <p>library(MissingDataGUI)</p>
-    
-
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-  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
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-
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-          </ul>
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diff --git a/docs/reference/test_if_dataframe.html b/docs/reference/test_if_dataframe.html
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-    <small class="dont-index">Source: <a href='https://github.com/njtierney/naniar/blob/master/R/utils.R'><code>R/utils.R</code></a></small>
-    <div class="hidden name"><code>test_if_dataframe.Rd</code></div>
-    </div>
-
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-    <p>Test if input is a data.frame</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>test_if_dataframe</span>(<span class='no'>x</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>x</th>
-      <td><p>object</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>an error if input (x) is a data.frame</p>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='kw'>if</span> (<span class='fl'>FALSE</span>) {
-<span class='co'># success</span>
-<span class='fu'>test_if_dataframe</span>(<span class='no'>airquality</span>)
-<span class='co'>#fail</span>
-<span class='no'>my_test</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/matrix.html'>matrix</a></span>(<span class='fl'>10</span>)
-<span class='fu'>test_if_dataframe</span>(<span class='no'>my_test</span>)
-}</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
-      <li><a href="#arguments">Arguments</a></li>
-      <li><a href="#value">Value</a></li>
-      <li><a href="#examples">Examples</a></li>
-    </ul>
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diff --git a/docs/reference/test_if_missing.html b/docs/reference/test_if_missing.html
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-    </div>
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-    <pre class="usage"><span class='fu'>test_if_missing</span>(<span class='no'>x</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
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-      <td><p>object</p></td>
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-    </table>
-
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-    <p>an error if input (x) is not specified</p>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='kw'>if</span> (<span class='fl'>FALSE</span>) {
-<span class='co'># success</span>
-<span class='no'>my_test</span> <span class='kw'>&lt;-</span> <span class='no'>x</span>
-<span class='fu'><a href='test_if_null.html'>test_if_null</a></span>(<span class='no'>my_test</span>)
-<span class='co'>#fail</span>
-<span class='fu'>test_if_missing</span>()
-}</div></pre>
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-    <pre class="usage"><span class='fu'>test_if_null</span>(<span class='no'>x</span>)</pre>
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-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>x</th>
-      <td><p>object</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>an error if input (x) is NULL</p>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='kw'>if</span> (<span class='fl'>FALSE</span>) {
-<span class='co'># success</span>
-<span class='fu'>test_if_null</span>(<span class='no'>airquality</span>)
-<span class='co'>#fail</span>
-<span class='no'>my_test</span> <span class='kw'>&lt;-</span> <span class='kw'>NULL</span>
-<span class='fu'>test_if_null</span>(<span class='no'>my_test</span>)
-}</div></pre>
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-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
-      <li><a href="#arguments">Arguments</a></li>
-      <li><a href="#value">Value</a></li>
-      <li><a href="#examples">Examples</a></li>
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-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
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-      <th>x</th>
-      <td><p>object</p></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>an error if input (x) is a shadow</p>
-    
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><span class='co'># NOT RUN {</span>
-<span class='co'># success</span>
-<span class='no'>aq_shadow</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='bind_shadow.html'>bind_shadow</a></span>(<span class='no'>airquality</span>)
-<span class='fu'>test_if_shadow</span>(<span class='no'>aq_shadow</span>)
-<span class='co'>#fail</span>
-<span class='fu'>test_if_shadow</span>(<span class='no'>airquality</span>)
-<span class='co'># }</span><div class='input'>
-</div></pre>
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diff --git a/docs/reference/unbinders.html b/docs/reference/unbinders.html
deleted file mode 100644
index 0bdb7807..00000000
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-This will also remove the nabular class from the data."><title>Unbind (remove) shadow from data, and vice versa — unbinders • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Unbind (remove) shadow from data, and vice versa — unbinders"><meta property="og:description" content="Remove the shadow variables (which end in _NA) from the data, or vice versa.
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-      <img src="../logo.png" class="logo" alt=""><h1>Unbind (remove) shadow from data, and vice versa</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/shadows.R" class="external-link"><code>R/shadows.R</code></a></small>
-      <div class="d-none name"><code>unbinders.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Remove the shadow variables (which end in <code>_NA</code>) from the data, or vice versa.
-This will also remove the <code>nabular</code> class from the data.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">unbind_shadow</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span>
-<span></span>
-<span><span class="fu">unbind_data</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
-<dd><p>data.frame containing shadow columns (created by <code><a href="bind_shadow.html">bind_shadow()</a></code>)</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p><code>data.frame</code> without shadow columns if using <code>unbind_shadow()</code>, or
-without the original data, if using <code>unbind_data()</code>.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># bind shadow columns</span></span></span>
-<span class="r-in"><span><span class="va">aq_sh</span> <span class="op">&lt;-</span> <span class="fu"><a href="bind_shadow.html">bind_shadow</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># print data</span></span></span>
-<span class="r-in"><span><span class="va">aq_sh</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 12</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    Ozone Solar.R  Wind  Temp Month   Day Ozone_NA Solar.R_NA Wind_NA Temp_NA</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>    41     190   7.4    67     5     1 !NA      !NA        !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>    36     118   8      72     5     2 !NA      !NA        !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>    12     149  12.6    74     5     3 !NA      !NA        !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>    18     313  11.5    62     5     4 !NA      !NA        !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>    <span style="color: #BB0000;">NA</span>      <span style="color: #BB0000;">NA</span>  14.3    56     5     5 NA       NA         !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>    28      <span style="color: #BB0000;">NA</span>  14.9    66     5     6 !NA      NA         !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>    23     299   8.6    65     5     7 !NA      !NA        !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>    19      99  13.8    59     5     8 !NA      !NA        !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>     8      19  20.1    61     5     9 !NA      !NA        !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>    <span style="color: #BB0000;">NA</span>     194   8.6    69     5    10 NA       !NA        !NA     !NA    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 2 more variables: Month_NA &lt;fct&gt;, Day_NA &lt;fct&gt;</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># remove shadow columns</span></span></span>
-<span class="r-in"><span><span class="fu">unbind_shadow</span><span class="op">(</span><span class="va">aq_sh</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 6</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    Ozone Solar.R  Wind  Temp Month   Day</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span>    41     190   7.4    67     5     1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span>    36     118   8      72     5     2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span>    12     149  12.6    74     5     3</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span>    18     313  11.5    62     5     4</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span>    <span style="color: #BB0000;">NA</span>      <span style="color: #BB0000;">NA</span>  14.3    56     5     5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span>    28      <span style="color: #BB0000;">NA</span>  14.9    66     5     6</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>    23     299   8.6    65     5     7</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span>    19      99  13.8    59     5     8</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span>     8      19  20.1    61     5     9</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span>    <span style="color: #BB0000;">NA</span>     194   8.6    69     5    10</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># remove data</span></span></span>
-<span class="r-in"><span><span class="fu">unbind_data</span><span class="op">(</span><span class="va">aq_sh</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 153 × 6</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    Ozone_NA Solar.R_NA Wind_NA Temp_NA Month_NA Day_NA</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span> </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> !NA      !NA        !NA     !NA     !NA      !NA   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> !NA      !NA        !NA     !NA     !NA      !NA   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> !NA      !NA        !NA     !NA     !NA      !NA   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> !NA      !NA        !NA     !NA     !NA      !NA   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> NA       NA         !NA     !NA     !NA      !NA   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> !NA      NA         !NA     !NA     !NA      !NA   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> !NA      !NA        !NA     !NA     !NA      !NA   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> !NA      !NA        !NA     !NA     !NA      !NA   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> !NA      !NA        !NA     !NA     !NA      !NA   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> NA       !NA        !NA     !NA     !NA      !NA   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 143 more rows</span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># errors when you don't use data with shadows</span></span></span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span> <span class="fu">unbind_data</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-in"><span> <span class="fu">unbind_shadow</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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diff --git a/docs/reference/update_shadow.html b/docs/reference/update_shadow.html
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-    <h1>Expand all shadow levels</h1>
-    <small class="dont-index">Source: <a href='https://github.com/njtierney/naniar/blob/master/R/shadow-recode.R'><code>R/shadow-recode.R</code></a></small>
-    <div class="hidden name"><code>update_shadow.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Internal function to appropriately expand and relevel all shadow variables to include a new suffix</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>update_shadow</span>(<span class='no'>data</span>, <span class='no'>suffix</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>data.frame</p></td>
-    </tr>
-    <tr>
-      <th>suffix</th>
-      <td><p>character vector</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>data.frame with adjusted levels</p>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'> <span class='kw'>if</span> (<span class='fl'>FALSE</span>) {
-<span class='no'>df</span> <span class='kw'>&lt;-</span> <span class='kw pkg'>tibble</span><span class='kw ns'>::</span><span class='fu'><a href='https://tibble.tidyverse.org/reference/tribble.html'>tribble</a></span>(
-~<span class='no'>wind</span>, ~<span class='no'>temp</span>,
--<span class='fl'>99</span>,    <span class='fl'>45</span>,
-<span class='fl'>68</span>,    <span class='fl'>NA</span>,
-<span class='fl'>72</span>,    <span class='fl'>25</span>
-)
-
-
-<span class='no'>dfs</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='bind_shadow.html'>bind_shadow</a></span>(<span class='no'>df</span>)
-
-<span class='fu'>update_shadow</span>(<span class='no'>dfs</span>, <span class='st'>"weee"</span>)
-<span class='fu'>update_shadow</span>(<span class='no'>dfs</span>, <span class='st'>"weee"</span>) <span class='kw'>%&gt;%</span> <span class='fu'><a href='what_levels.html'>what_levels</a></span>()
-}</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
-    <h2>Contents</h2>
-    <ul class="nav nav-pills nav-stacked">
-      <li><a href="#arguments">Arguments</a></li>
-      <li><a href="#value">Value</a></li>
-      <li><a href="#examples">Examples</a></li>
-    </ul>
-
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diff --git a/docs/reference/what_levels.html b/docs/reference/what_levels.html
deleted file mode 100644
index ed3c3723..00000000
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-    <small class="dont-index">Source: <a href='https://github.com/njtierney/naniar/blob/master/R/utils.R'><code>R/utils.R</code></a></small>
-    <div class="hidden name"><code>what_levels.Rd</code></div>
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-    <p>this function is used internally to check what the levels are of the dataframe.</p>
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diff --git a/docs/reference/where.html b/docs/reference/where.html
deleted file mode 100644
index 8c8b6581..00000000
--- a/docs/reference/where.html
+++ /dev/null
@@ -1,129 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="This function is used inside recode_shadow to help evaluate the formula
-call effectively. .where is a special function designed for use in
-recode_shadow, and you shouldn't use it outside of it"><title>Split a call into two components with a useful verb name — where • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Split a call into two components with a useful verb name — where"><meta property="og:description" content="This function is used inside recode_shadow to help evaluate the formula
-call effectively. .where is a special function designed for use in
-recode_shadow, and you shouldn't use it outside of it"><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-      <img src="../logo.png" class="logo" alt=""><h1>Split a call into two components with a useful verb name</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/shadow-recode.R" class="external-link"><code>R/shadow-recode.R</code></a></small>
-      <div class="d-none name"><code>where.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>This function is used inside <code>recode_shadow</code> to help evaluate the formula
-call effectively. <code>.where</code> is a special function designed for use in
-<code>recode_shadow</code>, and you shouldn't use it outside of it</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">.where</span><span class="op">(</span><span class="va">...</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>...</dt>
-<dd><p>case_when style formula</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>a list of "condition" and "suffix" arguments</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
-<span class="r-in"><span><span class="va">df</span> <span class="op">&lt;-</span> <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/tribble.html" class="external-link">tribble</a></span><span class="op">(</span></span></span>
-<span class="r-in"><span><span class="op">~</span><span class="va">wind</span>, <span class="op">~</span><span class="va">temp</span>,</span></span>
-<span class="r-in"><span><span class="op">-</span><span class="fl">99</span>,    <span class="fl">45</span>,</span></span>
-<span class="r-in"><span><span class="fl">68</span>,    <span class="cn">NA</span>,</span></span>
-<span class="r-in"><span><span class="fl">72</span>,    <span class="fl">25</span></span></span>
-<span class="r-in"><span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">dfs</span> <span class="op">&lt;-</span> <span class="fu"><a href="bind_shadow.html">bind_shadow</a></span><span class="op">(</span><span class="va">df</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu"><a href="recode_shadow.html">recode_shadow</a></span><span class="op">(</span><span class="va">dfs</span>,</span></span>
-<span class="r-in"><span>              temp <span class="op">=</span> <span class="fu">.where</span><span class="op">(</span><span class="va">wind</span> <span class="op">==</span> <span class="op">-</span><span class="fl">99</span> <span class="op">~</span> <span class="st">"bananas"</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="op">}</span></span></span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
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diff --git a/docs/reference/where_na.html b/docs/reference/where_na.html
deleted file mode 100644
index 1c142ad5..00000000
--- a/docs/reference/where_na.html
+++ /dev/null
@@ -1,165 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Internal function that is short for which(is.na(x), arr.ind = TRUE).
-Creates array index locations of missing values in a dataframe."><title>Which rows and cols contain missings? — where_na • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Which rows and cols contain missings? — where_na"><meta property="og:description" content="Internal function that is short for which(is.na(x), arr.ind = TRUE).
-Creates array index locations of missing values in a dataframe."><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-<div class="row">
-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.png" class="logo" alt=""><h1>Which rows and cols contain missings?</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/where-na.R" class="external-link"><code>R/where-na.R</code></a></small>
-      <div class="d-none name"><code>where_na.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>Internal function that is short for <code>which(is.na(x), arr.ind = TRUE)</code>.
-Creates array index locations of missing values in a dataframe.</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">where_na</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
-<dd><p>a dataframe</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>a matrix with columns "row" and "col", which refer to the row and
-column that identify the position of a missing value in a dataframe</p>
-    </div>
-    <div class="section level2">
-    <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
-    <div class="dont-index"><p><code><a href="which_na.html">which_na()</a></code></p></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">where_na</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>       row col</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [1,]   5   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [2,]  10   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [3,]  25   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [4,]  26   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [5,]  27   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [6,]  32   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [7,]  33   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [8,]  34   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [9,]  35   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [10,]  36   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [11,]  37   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [12,]  39   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [13,]  42   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [14,]  43   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [15,]  45   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [16,]  46   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [17,]  52   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [18,]  53   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [19,]  54   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [20,]  55   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [21,]  56   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [22,]  57   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [23,]  58   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [24,]  59   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [25,]  60   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [26,]  61   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [27,]  65   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [28,]  72   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [29,]  75   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [30,]  83   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [31,]  84   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [32,] 102   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [33,] 103   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [34,] 107   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [35,] 115   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [36,] 119   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [37,] 150   1</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [38,]   5   2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [39,]   6   2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [40,]  11   2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [41,]  27   2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [42,]  96   2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [43,]  97   2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [44,]  98   2</span>
-<span class="r-in"><span><span class="fu">where_na</span><span class="op">(</span><span class="va">oceanbuoys</span><span class="op">$</span><span class="va">sea_temp_c</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 463 481 637</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
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diff --git a/docs/reference/which_are_shade.html b/docs/reference/which_are_shade.html
deleted file mode 100644
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--- a/docs/reference/which_are_shade.html
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@@ -1,114 +0,0 @@
-<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="This function tells us which variables contain shade information"><title>Which variables are shades? — which_are_shade • naniar</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Which variables are shades? — which_are_shade"><meta property="og:description" content="This function tells us which variables contain shade information"><meta property="og:image" content="http://naniar.njtierney.com/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-      <img src="../logo.png" class="logo" alt=""><h1>Which variables are shades?</h1>
-      <small class="dont-index">Source: <a href="https://github.com/njtierney/naniar/blob/HEAD/R/shade.R" class="external-link"><code>R/shade.R</code></a></small>
-      <div class="d-none name"><code>which_are_shade.Rd</code></div>
-    </div>
-
-    <div class="ref-description section level2">
-    <p>This function tells us which variables contain shade information</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">which_are_shade</span><span class="op">(</span><span class="va">.tbl</span><span class="op">)</span></span></code></pre></div>
-    </div>
-
-    <div class="section level2">
-    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>.tbl</dt>
-<dd><p>a data.frame or tbl</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>numeric - which column numbers contain shade information</p>
-    </div>
-
-    <div class="section level2">
-    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="va">df_shadow</span> <span class="op">&lt;-</span> <span class="fu"><a href="bind_shadow.html">bind_shadow</a></span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">which_are_shade</span><span class="op">(</span><span class="va">df_shadow</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   Ozone_NA Solar.R_NA    Wind_NA    Temp_NA   Month_NA     Day_NA </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>          7          8          9         10         11         12 </span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
-    </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
-    </nav></aside></div>
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diff --git a/docs/reference/which_na.html b/docs/reference/which_na.html
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--- a/docs/reference/which_na.html
+++ /dev/null
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-    <p>Equivalent to <code>which(is.na())</code> - returns integer locations of missing values.</p>
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-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">which_na</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span></code></pre></div>
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-    <dl><dt>x</dt>
-<dd><p>a dataframe</p></dd>
-
-</dl></div>
-    <div class="section level2">
-    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
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-<p>integer locations of missing values.</p>
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-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="fu">which_na</span><span class="op">(</span><span class="va">airquality</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [1]   5  10  25  26  27  32  33  34  35  36  37  39  42  43  45  46  52  53  54</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [20]  55  56  57  58  59  60  61  65  72  75  83  84 102 103 107 115 119 150 158</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [39] 159 164 180 249 250 251</span>
-<span class="r-in"><span></span></span>
-</code></pre></div>
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-    <div class="hidden name"><code>which_var_na.Rd</code></div>
-    </div>
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-    
-    <p>It can be helpful when writing other functions to just return the names
-of the variables that contain missing values.</p>
-    
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-
-    <pre class="usage"><span class='fu'>which_var_na</span>(<span class='no'>data</span>)</pre>
-    
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>a data.frame</p></td>
-    </tr>
-    </table>
-    
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>character vector of variable names</p>
-    
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-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><span class='co'># NOT RUN {</span>
-<span class='fu'>which_var_na</span>(<span class='no'>airquality</span>)
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-<span class='fu'>which_var_na</span>(<span class='no'>iris</span>)
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-    <loc>http://naniar.njtierney.com/reference/common_na_numbers.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/common_na_strings.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/draw_key.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/gather_shadow.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/geom_miss_point.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/geom_missing_point.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/gg_miss_case.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/gg_miss_case_cumsum.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/gg_miss_fct.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/gg_miss_span.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/gg_miss_upset.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/gg_miss_var.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/gg_miss_var_cumsum.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/gg_miss_which.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/gg_missing_case.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/gg_missing_var.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/gg_missing_which.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/group_by_fun.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/impute_below.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/impute_below_all.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/impute_below_at.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/impute_below_if.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/impute_knn.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/impute_mean.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/impute_median.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/impute_shift.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/impute_shift_at.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/impute_shift_if.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/index.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/is_shade.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/is_shadow.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/label_miss_1d.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/label_miss_2d.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/label_missing_1d.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/label_missing_2d.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/label_missings.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/label_na.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/label_shadow.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/label_shadow_matrix.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/mcar_test.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/miss-complete-case-pct.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/miss-complete-case-prop.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/miss-complete-var-pct.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/miss-complete-var-prop.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/miss-pct-prop-defunct.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/miss_case_cumsum.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/miss_case_pct.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/miss_case_prop.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/miss_case_summary.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/miss_case_table.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/miss_df_pct.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/miss_prop_summary.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/miss_scan_count.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/miss_summary.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/miss_var_cumsum.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/miss_var_pct.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/miss_var_prop.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/miss_var_run.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/miss_var_span.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/miss_var_summary.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/miss_var_table.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/miss_var_which.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/n-var-case-complete.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/n-var-case-miss.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/n_complete.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/n_complete_row.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/n_miss.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/n_miss_row.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/nabular.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/naniar-ggproto.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/naniar.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/narnia-ggproto.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/narnia.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/new_nabular.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/new_shade.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/new_shadow.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/oceanbuoys.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/pct-miss-complete-case.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/pct-miss-complete-var.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/pct_complete.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/pct_miss.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/pedestrian.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/percent_missing_case.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/percent_missing_df.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/percent_missing_var.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/plotly_helpers.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/prop-miss-complete-case.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/prop-miss-complete-var.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/prop_complete.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/prop_complete_row.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/prop_miss.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/prop_miss_row.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/recode_shadow.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/reexports.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/replace_to_na.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/replace_with_na.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/replace_with_na_all.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/replace_with_na_at.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/replace_with_na_if.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/riskfactors.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/scoped-impute_mean.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/scoped-impute_median.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/set-prop-n-miss.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/shade.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/shadow_expand_relevel.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/shadow_long.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/shadow_shift.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/shadow_shift.numeric.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/stat_miss_point.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/stat_missing_point.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/summarise_missingness.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/summary_missing_case.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/summary_missing_var.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/table_missing_case.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/table_missing_var.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/tao.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/test_if_dataframe.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/test_if_missing.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/test_if_null.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/test_if_shadow.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/unbinders.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/update_shadow.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/what_levels.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/where.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/where_na.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/which_are_shade.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/which_na.html</loc>
-  </url>
-  <url>
-    <loc>http://naniar.njtierney.com/reference/which_var_na.html</loc>
-  </url>
-</urlset>

From 3cc6ff0e56d710237c28c5e9674d4d0046a56f9b Mon Sep 17 00:00:00 2001
From: olivroy <olivierroy71@hotmail.com>
Date: Fri, 15 Mar 2024 11:57:25 -0400
Subject: [PATCH 2/9] Delete old config files + update gh ations

---
 .github/workflows/R-CMD-check.yaml            |   5 +-
 .github/workflows/pkgdown.yaml                |   4 +-
 .travis.yml                                   |  45 ----------------
 appveyor.yml                                  |  50 ------------------
 .../figure-html/ggmissing-theme-1.png         | Bin 69109 -> 0 bytes
 .../figure-html/unnamed-chunk-1-1.png         | Bin 21030 -> 0 bytes
 .../figure-html/unnamed-chunk-2-1.png         | Bin 22896 -> 0 bytes
 .../figure-html/unnamed-chunk-2-2.png         | Bin 61288 -> 0 bytes
 .../figure-html/vis-dat-1.png                 | Bin 30195 -> 0 bytes
 .../vis-miss-cluster-vanilla-1.png            | Bin 16382 -> 0 bytes
 10 files changed, 5 insertions(+), 99 deletions(-)
 delete mode 100644 .travis.yml
 delete mode 100644 appveyor.yml
 delete mode 100755 vignettes/getting-started-w-narnia_files/figure-html/ggmissing-theme-1.png
 delete mode 100755 vignettes/getting-started-w-narnia_files/figure-html/unnamed-chunk-1-1.png
 delete mode 100755 vignettes/getting-started-w-narnia_files/figure-html/unnamed-chunk-2-1.png
 delete mode 100755 vignettes/getting-started-w-narnia_files/figure-html/unnamed-chunk-2-2.png
 delete mode 100755 vignettes/getting-started-w-narnia_files/figure-html/vis-dat-1.png
 delete mode 100755 vignettes/getting-started-w-narnia_files/figure-html/vis-miss-cluster-vanilla-1.png

diff --git a/.github/workflows/R-CMD-check.yaml b/.github/workflows/R-CMD-check.yaml
index 52c2b277..14159b77 100644
--- a/.github/workflows/R-CMD-check.yaml
+++ b/.github/workflows/R-CMD-check.yaml
@@ -18,7 +18,7 @@ jobs:
       fail-fast: false
       matrix:
         config:
-          - {os: macOS-latest,   r: 'release'}
+          - {os: macos-latest,   r: 'release'}
           - {os: windows-latest, r: 'release'}
           - {os: ubuntu-latest,   r: 'devel', http-user-agent: 'release'}
           - {os: ubuntu-latest,   r: 'release'}
@@ -29,7 +29,7 @@ jobs:
       R_KEEP_PKG_SOURCE: yes
 
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v4
 
       - uses: r-lib/actions/setup-pandoc@v2
 
@@ -47,3 +47,4 @@ jobs:
       - uses: r-lib/actions/check-r-package@v2
         with:
           upload-snapshots: true
+          build_args: 'c("--no-manual","--compact-vignettes=gs+qpdf")'
diff --git a/.github/workflows/pkgdown.yaml b/.github/workflows/pkgdown.yaml
index ed7650c7..a7276e85 100644
--- a/.github/workflows/pkgdown.yaml
+++ b/.github/workflows/pkgdown.yaml
@@ -22,7 +22,7 @@ jobs:
     permissions:
       contents: write
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
 
       - uses: r-lib/actions/setup-pandoc@v2
 
@@ -41,7 +41,7 @@ jobs:
 
       - name: Deploy to GitHub pages 🚀
         if: github.event_name != 'pull_request'
-        uses: JamesIves/github-pages-deploy-action@v4.4.1
+        uses: JamesIves/github-pages-deploy-action@v4.5.0
         with:
           clean: false
           branch: gh-pages
diff --git a/.travis.yml b/.travis.yml
deleted file mode 100644
index 5f729fd5..00000000
--- a/.travis.yml
+++ /dev/null
@@ -1,45 +0,0 @@
-# R for travis: see documentation at https://docs.travis-ci.com/user/languages/r
-
-language: r
-os:
-  - linux
-  - osx
-r:
-  - oldrel
-  - release
-  - devel
-sudo: false
-dist: trusty
-cache: packages
-warnings_are_errors: true
-
-r_packages:
-  - knitr
-  - rmarkdown
-  - devtools
-  - testthat
-  - covr
-
-email:
-  on_success: change
-  on_failure: change
-
-env:
-  global:
-    - _R_CHECK_FORCE_SUGGESTS_=false
-
-after_success:
-  - bash <(curl -s https://codecov.io/bash)
-  - Rscript -e 'covr::codecov()'
-
-before_deploy: Rscript -e 'remotes::install_cran("pkgdown")'
-deploy:
-  provider: script
-  script: Rscript -e 'pkgdown::deploy_site_github()'
-  skip_cleanup: true
-
-before_cache: Rscript -e 'remotes::install_cran("pkgdown")'
-deploy:
-  provider: script
-  script: Rscript -e 'pkgdown::deploy_site_github()'
-  skip_cleanup: true
diff --git a/appveyor.yml b/appveyor.yml
deleted file mode 100644
index 8df6b7aa..00000000
--- a/appveyor.yml
+++ /dev/null
@@ -1,50 +0,0 @@
-# DO NOT CHANGE the "init" and "install" sections below
-
-# Download script file from GitHub
-init:
-  ps: |
-        $ErrorActionPreference = "Stop"
-        Invoke-WebRequest http://raw.github.com/krlmlr/r-appveyor/master/scripts/appveyor-tool.ps1 -OutFile "..\appveyor-tool.ps1"
-        Import-Module '..\appveyor-tool.ps1'
-
-install:
-  ps: Bootstrap
-
-# Adapt as necessary starting from here
-
-build_script:
-  - travis-tool.sh install_deps
-  #- travis-tool.sh install_github njtierney/visdat
-
-test_script:
-  - travis-tool.sh run_tests
-
-on_failure:
-  - 7z a failure.zip *.Rcheck\*
-  - appveyor PushArtifact failure.zip
-
-on_success:
-  - Rscript -e 'covr::codecov()'
-
-environment:
-  global:
-    _R_CHECK_FORCE_SUGGESTS_: false
-
-artifacts:
-  - path: '*.Rcheck\**\*.log'
-    name: Logs
-
-  - path: '*.Rcheck\**\*.out'
-    name: Logs
-
-  - path: '*.Rcheck\**\*.fail'
-    name: Logs
-
-  - path: '*.Rcheck\**\*.Rout'
-    name: Logs
-
-  - path: '\*_*.tar.gz'
-    name: Bits
-
-  - path: '\*_*.zip'
-    name: Bits
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diff --git a/vignettes/getting-started-w-narnia_files/figure-html/vis-miss-cluster-vanilla-1.png b/vignettes/getting-started-w-narnia_files/figure-html/vis-miss-cluster-vanilla-1.png
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Bx&r_J


From 0430ab07b89e951f9431284ccf30bcabd320a7a5 Mon Sep 17 00:00:00 2001
From: olivroy <olivierroy71@hotmail.com>
Date: Fri, 15 Mar 2024 11:58:50 -0400
Subject: [PATCH 3/9] Update links in README

---
 README.Rmd | 6 +++---
 README.md  | 5 ++---
 2 files changed, 5 insertions(+), 6 deletions(-)

diff --git a/README.Rmd b/README.Rmd
index d79a0e27..2ab49928 100644
--- a/README.Rmd
+++ b/README.Rmd
@@ -12,15 +12,15 @@ knitr::opts_chunk$set(
 )
 ```
 
-# naniar <a href="http://naniar.njtierney.com/"><img src="man/figures/logo.png" align="right" height="138" /></a>
+# naniar <a href="https://naniar.njtierney.com/"><img src="man/figures/logo.png" align="right" height="138" /></a>
 
 <!-- badges: start -->
-[![R build status](https://github.com/njtierney/naniar/workflows/R-CMD-check/badge.svg)](https://github.com/njtierney/naniar)
+[![R-CMD-check](https://github.com/njtierney/naniar/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/njtierney/naniar/actions/workflows/R-CMD-check.yaml)
 [![Coverage Status](https://img.shields.io/codecov/c/github/njtierney/naniar/master.svg)](https://app.codecov.io/github/njtierney/naniar?branch=master)
 [![CRAN Status Badge](https://www.r-pkg.org/badges/version/naniar)](https://cran.r-project.org/package=naniar)
 [![CRAN Downloads Each Month](https://cranlogs.r-pkg.org/badges/naniar)](https://CRAN.R-project.org/package=naniar)
 [![lifecycle](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://lifecycle.r-lib.org/articles/stages.html)
-  <!-- badges: end -->
+<!-- badges: end -->
 
 `naniar` provides principled, tidy ways to summarise, visualise, and manipulate missing data with minimal deviations from the workflows in ggplot2 and tidy data. It does this by providing:
 
diff --git a/README.md b/README.md
index ec007a67..a4d83916 100644
--- a/README.md
+++ b/README.md
@@ -1,12 +1,11 @@
 
 <!-- README.md is generated from README.Rmd. Please edit that file -->
 
-# naniar <a href="http://naniar.njtierney.com/"><img src="man/figures/logo.png" align="right" height="138" /></a>
+# naniar <a href="https://naniar.njtierney.com/"><img src="man/figures/logo.png" align="right" height="138" /></a>
 
 <!-- badges: start -->
 
-[![R build
-status](https://github.com/njtierney/naniar/workflows/R-CMD-check/badge.svg)](https://github.com/njtierney/naniar)
+[![R-CMD-check](https://github.com/njtierney/naniar/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/njtierney/naniar/actions/workflows/R-CMD-check.yaml)
 [![Coverage
 Status](https://img.shields.io/codecov/c/github/njtierney/naniar/master.svg)](https://app.codecov.io/github/njtierney/naniar?branch=master)
 [![CRAN Status

From a9e47f46f6f4edb31d76ba16f2ab4dea7dbf15d8 Mon Sep 17 00:00:00 2001
From: olivroy <olivierroy71@hotmail.com>
Date: Fri, 15 Mar 2024 12:00:33 -0400
Subject: [PATCH 4/9] Rename vignette + add redirects + update links

---
 DESCRIPTION                                            | 2 +-
 README.Rmd                                             | 4 ++--
 README.md                                              | 4 ++--
 _pkgdown.yml                                           | 6 ++++--
 vignettes/naniar-visualisation.Rmd                     | 2 +-
 vignettes/{getting-started-w-naniar.Rmd => naniar.Rmd} | 2 +-
 vignettes/special-missing-values.Rmd                   | 4 ++--
 7 files changed, 13 insertions(+), 11 deletions(-)
 rename vignettes/{getting-started-w-naniar.Rmd => naniar.Rmd} (99%)

diff --git a/DESCRIPTION b/DESCRIPTION
index d567be0b..d68ece68 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -135,7 +135,7 @@ Collate:
     'utils.R'
     'where-na.R'
 URL: https://github.com/njtierney/naniar,
-    http://naniar.njtierney.com/
+    https://naniar.njtierney.com/
 BugReports: https://github.com/njtierney/naniar/issues
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
diff --git a/README.Rmd b/README.Rmd
index 2ab49928..cc6ff546 100644
--- a/README.Rmd
+++ b/README.Rmd
@@ -40,7 +40,7 @@ knitr::opts_chunk$set(
     - `gg_miss_case()`
     - `gg_miss_fct()`
 
-For more details on the workflow and theory underpinning naniar, read the vignette [Getting started with naniar](https://naniar.njtierney.com/articles/getting-started-w-naniar.html). 
+For more details on the workflow and theory underpinning naniar, read the vignette [Getting started with naniar](https://naniar.njtierney.com/articles/naniar.html). 
 
 For a short primer on the data visualisation available in naniar, read the vignette [Gallery of Missing Data Visualisations](https://naniar.njtierney.com/articles/naniar-visualisation.html).
 
@@ -217,7 +217,7 @@ airquality %>%
 
 ```
 
-You can read more about all of these functions in the vignette ["Getting Started with naniar"](https://naniar.njtierney.com/articles/getting-started-w-naniar.html).
+You can read more about all of these functions in the vignette ["Getting Started with naniar"](https://naniar.njtierney.com/articles/naniar.html).
 
 # Statistical tests of missingness
 
diff --git a/README.md b/README.md
index a4d83916..00fddd5a 100644
--- a/README.md
+++ b/README.md
@@ -39,7 +39,7 @@ ggplot2 and tidy data. It does this by providing:
 
 For more details on the workflow and theory underpinning naniar, read
 the vignette [Getting started with
-naniar](https://naniar.njtierney.com/articles/getting-started-w-naniar.html).
+naniar](https://naniar.njtierney.com/articles/naniar.html).
 
 For a short primer on the data visualisation available in naniar, read
 the vignette [Gallery of Missing Data
@@ -369,7 +369,7 @@ airquality %>%
 
 You can read more about all of these functions in the vignette [“Getting
 Started with
-naniar”](https://naniar.njtierney.com/articles/getting-started-w-naniar.html).
+naniar”](https://naniar.njtierney.com/articles/naniar.html).
 
 # Statistical tests of missingness
 
diff --git a/_pkgdown.yml b/_pkgdown.yml
index 5ac2e685..c9813663 100644
--- a/_pkgdown.yml
+++ b/_pkgdown.yml
@@ -1,4 +1,4 @@
-url: http://naniar.njtierney.com/
+url: https://naniar.njtierney.com/
 template:
   bootstrap: 5
   bootswatch: flatly
@@ -11,7 +11,7 @@ authors:
   Nick Tierney:
     href: https://njtierney.com/
   Di Cook:
-    href: http://www.dicook.org/
+    href: https://www.dicook.org/
   Miles McBain:
     href: https://milesmcbain.xyz/
   Colin Fay:
@@ -134,3 +134,5 @@ navbar:
   - text: News
     href: news/index.html
 
+redirects:
+ - ["articles/getting-started-w-naniar.html", "articles/naniar.html"]
diff --git a/vignettes/naniar-visualisation.Rmd b/vignettes/naniar-visualisation.Rmd
index cc7789e9..fd07ded5 100644
--- a/vignettes/naniar-visualisation.Rmd
+++ b/vignettes/naniar-visualisation.Rmd
@@ -17,7 +17,7 @@ knitr::opts_chunk$set(fig.align = "center",
 
 ```
 
-There are a variety of different plots to explore missing data available in the naniar package. This vignette simply showcases all of the visualisations. If you would like to know more about the philosophy of the `naniar` package, you should read the vignette [Getting Started with naniar](http://naniar.njtierney.com/articles/getting-started-w-naniar.html).
+There are a variety of different plots to explore missing data available in the naniar package. This vignette simply showcases all of the visualisations. If you would like to know more about the philosophy of the `naniar` package, you should read `vignette("naniar")`.
 
 A key point to remember with the visualisation tools in `naniar` is that there is a way to get the data from the plot out from the visualisation.
 
diff --git a/vignettes/getting-started-w-naniar.Rmd b/vignettes/naniar.Rmd
similarity index 99%
rename from vignettes/getting-started-w-naniar.Rmd
rename to vignettes/naniar.Rmd
index add8786d..282d4b24 100644
--- a/vignettes/getting-started-w-naniar.Rmd
+++ b/vignettes/naniar.Rmd
@@ -195,7 +195,7 @@ the function `replace_with_na`. This function is the compliment to
 - `tidyr::replace_na`: Missing values turns into a value (NA --> -99)
 - `naniar::replace_with_na`: Value becomes a missing value (-99 --> NA)
 
-You can read more about this in the vignette ["Replacing values with NA"](http://naniar.njtierney.com/articles/replace-with-na.html)
+You can read more about this in the vignette ["Replacing values with NA"](https://naniar.njtierney.com/articles/replace-with-na.html)
 
 # Tidy Missing Data: The Shadow Matrix
 
diff --git a/vignettes/special-missing-values.Rmd b/vignettes/special-missing-values.Rmd
index 5ae8fc47..b8bde01b 100644
--- a/vignettes/special-missing-values.Rmd
+++ b/vignettes/special-missing-values.Rmd
@@ -48,7 +48,7 @@ We create `nabular` data by `bind`ing the shadow to the data:
 bind_shadow(oceanbuoys)
 ```
 
-This keeps the data values tied to their missingness, and has great benefits for exploring missing and imputed values in data. See the vignettes [Getting Started with naniar](http://naniar.njtierney.com/articles/getting-started-w-naniar.html) and [Exploring Imputations with naniar](http://naniar.njtierney.com/articles/exploring-imputed-values.html) for more details.
+This keeps the data values tied to their missingness, and has great benefits for exploring missing and imputed values in data. See the vignettes [Getting Started with naniar](https://naniar.njtierney.com/articles/naniar.html) and [Exploring Imputations with naniar](http://naniar.njtierney.com/articles/exploring-imputed-values.html) for more details.
 
 # Recoding missing values
 
@@ -103,6 +103,6 @@ Under the hood, this special missing value is recoded as a new factor level in t
 Some examples of using `recode_shadow` in a workflow will be discussed in more detail in the near future, for the moment, here is a recommended workflow:
 
 * Use `recode_shadow()` with actual data
-* Replacing the previous actual values using `replace_with_na()` (see the vignette on [replacing values with NA](http://naniar.njtierney.com/articles/replace-with-na.html))
+* Replacing the previous actual values using `replace_with_na()` (see the vignette on [replacing values with NA](https://naniar.njtierney.com/articles/replace-with-na.html))
 * Explore missings where special cases are considered
 * Explore imputed values, looking at these special cases

From fbde17334932732fa48a807ee44f9036aac72c78 Mon Sep 17 00:00:00 2001
From: olivroy <olivierroy71@hotmail.com>
Date: Fri, 15 Mar 2024 12:01:37 -0400
Subject: [PATCH 5/9] Add links to vignettes in reference.

---
 _pkgdown.yml | 8 ++++++--
 1 file changed, 6 insertions(+), 2 deletions(-)

diff --git a/_pkgdown.yml b/_pkgdown.yml
index c9813663..27c0e190 100644
--- a/_pkgdown.yml
+++ b/_pkgdown.yml
@@ -33,6 +33,7 @@ reference:
 - title: Create special missing values
   desc: |
     Create special missing values so that they don't get lost!
+    See `vignette("special-missing")`.
   contents: recode_shadow
 - title: Visualisation
   desc: |
@@ -67,14 +68,16 @@ reference:
   contents: starts_with("add_")
 - title: Replacing values with and to NA
   desc: |
-    Functions to help replace certain values with NA, which includes scoped variants (_at, _if, _all) that take formulas for flexible approachs
+    Functions to help replace certain values with NA, which includes scoped variants
+    (_at, _if, _all) that take formulas for flexible approachs. `vignette("replace-with-na")`
   contents:
   - starts_with("replace_with_na")
   - replace_to_na
   - replace_na_with
 - title: Imputation helpers
   desc: |
-    Simple imputation methods for exploring visualisation and missingness structure
+    Simple imputation methods for exploring visualisation and missingness structure.
+    See `vignette("exploring-imputed-values")` for more details.
   contents:
   - starts_with("impute_")
   - set-prop-n-miss
@@ -111,6 +114,7 @@ reference:
   desc: |
     Custom ggplot geoms built to extend ggplot for missing values
   contents: naniar-ggproto
+
 navbar:
   left:
   - text: Getting Started

From b4994fccb78098510df5cb2dc27220f05cd018c9 Mon Sep 17 00:00:00 2001
From: olivroy <olivierroy71@hotmail.com>
Date: Fri, 15 Mar 2024 12:02:00 -0400
Subject: [PATCH 6/9] Update pkgdown config

---
 _pkgdown.yml | 41 +++++++++++++++++++++--------------------
 1 file changed, 21 insertions(+), 20 deletions(-)

diff --git a/_pkgdown.yml b/_pkgdown.yml
index 27c0e190..ba42be6f 100644
--- a/_pkgdown.yml
+++ b/_pkgdown.yml
@@ -116,27 +116,28 @@ reference:
   contents: naniar-ggproto
 
 navbar:
-  left:
-  - text: Getting Started
-    href: articles/getting-started-w-naniar.html
-  - text: Gallery
-    href: articles/naniar-visualisation.html
-  - text: Articles
-    menu:
-    - text: Replace with NA
-      href: articles/replace-with-na.html
-    - text: Special Missings
-      href: articles/special-missing-values.html
-    - text: Exploring Imputations
-      href: articles/exploring-imputed-values.html
-  - text: Reference
-    href: reference/index.html
-  - text: News
-    releases:
-  - text: "Version 1.1.0"
+  structure:
+    left: [intro, gallery, articles, reference, news]
+  components:
+    gallery:
+      text: Gallery
+      href: articles/naniar-visualisation.html
+    articles:
+      text: Articles
+      menu:
+      - text: Replace with NA
+        href: articles/replace-with-na.html
+      - text: Special Missings
+        href: articles/special-missing-values.html
+      - text: Exploring Imputations
+        href: articles/exploring-imputed-values.html
+
+news:
+  releases:
+  - text: Version 1.1.0
     href: https://www.njtierney.com/post/2024/03/04/naniar-version-1-1-0-prince-caspian/
-  - text: News
-    href: news/index.html
+  - text: Version 1.0.0
+    href: https://www.njtierney.com/post/2023/02/07/naniar-version-1/
 
 redirects:
  - ["articles/getting-started-w-naniar.html", "articles/naniar.html"]

From 3cf9be8d122bcd03e0def086382f7b257fe2156d Mon Sep 17 00:00:00 2001
From: olivroy <olivierroy71@hotmail.com>
Date: Fri, 15 Mar 2024 12:06:55 -0400
Subject: [PATCH 7/9] Add comment + remove covr from Suggests

---
 DESCRIPTION                                  | 1 -
 tests/testthat/test-special-missing-values.R | 5 +++--
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index d68ece68..5bde86fb 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -47,7 +47,6 @@ Suggests:
     testthat (>= 3.0.0),
     rpart,
     rpart.plot,
-    covr,
     gridExtra,
     wakefield,
     vdiffr,
diff --git a/tests/testthat/test-special-missing-values.R b/tests/testthat/test-special-missing-values.R
index 137ac37b..d8ebd074 100644
--- a/tests/testthat/test-special-missing-values.R
+++ b/tests/testthat/test-special-missing-values.R
@@ -139,10 +139,11 @@ test_that("special missings are the same for grouped and ungrouped data", {
 test_that("special missings class is maintained for grouped and ungrouped data", {
   skip_on_cran()
   skip_on_ci()
+  # FIXME failing test?
   expect_equal(class(aq_grouped_recoded$Ozone_NA),
                class(aq_recoded$Ozone_NA))
-  expect_true(is_shade(aq_grouped_recoded$Ozone_NA),
-              is_shade(aq_recoded$Ozone_NA))
+  expect_true(is_shade(aq_grouped_recoded$Ozone_NA))
+  expect_true(is_shade(aq_recoded$Ozone_NA))
 })
 
 test_that("shadow_expand_relevel returns shadows inside a data.frame", {

From 85f2737688ad02b1ba2dfb1e449d103c375da84e Mon Sep 17 00:00:00 2001
From: olivroy <olivierroy71@hotmail.com>
Date: Fri, 15 Mar 2024 12:25:13 -0400
Subject: [PATCH 8/9] Minor tweaks in docs

---
 R/geom-miss-point.R       | 30 +++++++++++++++---------------
 R/gg-miss-case.R          |  2 +-
 R/gg-miss-fct.R           |  2 +-
 R/gg-miss-span.R          |  2 +-
 R/gg-miss-var-cumsum.R    |  2 +-
 R/gg-miss-var.R           |  2 +-
 R/gg-miss-which.R         |  2 +-
 _pkgdown.yml              |  2 +-
 man/geom_miss_point.Rd    | 10 ++++------
 man/gg_miss_case.Rd       |  2 +-
 man/gg_miss_fct.Rd        |  2 +-
 man/gg_miss_span.Rd       |  2 +-
 man/gg_miss_var.Rd        |  2 +-
 man/gg_miss_var_cumsum.Rd |  2 +-
 man/gg_miss_which.Rd      |  2 +-
 15 files changed, 32 insertions(+), 34 deletions(-)

diff --git a/R/geom-miss-point.R b/R/geom-miss-point.R
index 459fa395..9d9a87d1 100644
--- a/R/geom-miss-point.R
+++ b/R/geom-miss-point.R
@@ -6,11 +6,11 @@
 #'   the same axis.
 #'
 #' @include legend-draw.R
-#' @name  geom_miss_point
-#' @title  geom_miss_point
-#' @note Warning message if na.rm = T is supplied.
+#' @name geom_miss_point
+#' @note Warning message if `na.rm = T` is supplied.
 #'
-#' @seealso [gg_miss_case()][gg_miss_case_cumsum()][gg_miss_fct()][gg_miss_span()][gg_miss_var()][gg_miss_var_cumsum()][gg_miss_which()]
+#' @seealso [gg_miss_case()] [gg_miss_case_cumsum()] [gg_miss_fct()]
+#'   [gg_miss_span()] [gg_miss_var()] [gg_miss_var_cumsum()] [gg_miss_which()]
 #'
 #' @param mapping Set of aesthetic mappings created by [ggplot2::aes()]
 #' or [ggplot2::aes_()]. If specified and `inherit.aes = TRUE`
@@ -79,17 +79,17 @@
 #'  facet_wrap(~Month)
 #'}
 #' @export
- geom_miss_point <- function(mapping = NULL,
-                             data = NULL,
-                             prop_below = 0.1,
-                             jitter = 0.05,
-                             stat = "miss_point",
-                             position = "identity",
-                             colour = ..missing..,
-                             na.rm = FALSE,
-                             show.legend = NA,
-                             inherit.aes = TRUE,
-                             ...) {
+geom_miss_point <- function(mapping = NULL,
+                            data = NULL,
+                            prop_below = 0.1,
+                            jitter = 0.05,
+                            stat = "miss_point",
+                            position = "identity",
+                            colour = ..missing..,
+                            na.rm = FALSE,
+                            show.legend = NA,
+                            inherit.aes = TRUE,
+                            ...) {
   layer(
     data = data,
     mapping = mapping,
diff --git a/R/gg-miss-case.R b/R/gg-miss-case.R
index a0849871..1bfae07d 100644
--- a/R/gg-miss-case.R
+++ b/R/gg-miss-case.R
@@ -12,7 +12,7 @@
 #'
 #' @return a ggplot object depicting the number of missings in a given case.
 #'
-#' @seealso [geom_miss_point()] [gg_miss_case_cumsum] [gg_miss_fct()] [gg_miss_span()] [gg_miss_var()] [gg_miss_var_cumsum()] [gg_miss_which()]
+#' @seealso [geom_miss_point()] [gg_miss_case_cumsum()] [gg_miss_fct()] [gg_miss_span()] [gg_miss_var()] [gg_miss_var_cumsum()] [gg_miss_which()]
 #'
 #' @examples
 #'
diff --git a/R/gg-miss-fct.R b/R/gg-miss-fct.R
index 452b476e..0e48ac6a 100644
--- a/R/gg-miss-fct.R
+++ b/R/gg-miss-fct.R
@@ -10,7 +10,7 @@
 #' @return ggplot object depicting the % missing of each factor level for
 #'   each variable.
 #'
-#' @seealso [geom_miss_point()] [gg_miss_case()] [gg_miss_case_cumsum] [gg_miss_span()] [gg_miss_var()] [gg_miss_var_cumsum()] [gg_miss_which()]
+#' @seealso [geom_miss_point()] [gg_miss_case()] [gg_miss_case_cumsum()] [gg_miss_span()] [gg_miss_var()] [gg_miss_var_cumsum()] [gg_miss_which()]
 #'
 #' @export
 #'
diff --git a/R/gg-miss-span.R b/R/gg-miss-span.R
index 69a01b43..dc12343f 100644
--- a/R/gg-miss-span.R
+++ b/R/gg-miss-span.R
@@ -10,7 +10,7 @@
 #' @param span_every integer describing the length of the span to be explored
 #' @param facet (optional) a single bare variable name, if you want to create a faceted plot.
 #'
-#' @seealso [geom_miss_point()] [gg_miss_case()] [gg_miss_case_cumsum] [gg_miss_fct()] [gg_miss_var()] [gg_miss_var_cumsum()] [gg_miss_which()]
+#' @seealso [geom_miss_point()] [gg_miss_case()] [gg_miss_case_cumsum()] [gg_miss_fct()] [gg_miss_var()] [gg_miss_var_cumsum()] [gg_miss_which()]
 
 #' @return ggplot2 showing the number of missings in a span (window, or breaksize)
 #' @export
diff --git a/R/gg-miss-var-cumsum.R b/R/gg-miss-var-cumsum.R
index 3e3ffc7f..a516fd0b 100644
--- a/R/gg-miss-var-cumsum.R
+++ b/R/gg-miss-var-cumsum.R
@@ -8,7 +8,7 @@
 #'
 #' @return a ggplot object showing the cumulative sum of missings over the variables
 #'
-#' @seealso [geom_miss_point()] [gg_miss_case()] [gg_miss_case_cumsum] [gg_miss_fct()] [gg_miss_span()] [gg_miss_var()] [gg_miss_which()]
+#' @seealso [geom_miss_point()] [gg_miss_case()] [gg_miss_case_cumsum()] [gg_miss_fct()] [gg_miss_span()] [gg_miss_var()] [gg_miss_which()]
 
 #' @export
 #'
diff --git a/R/gg-miss-var.R b/R/gg-miss-var.R
index 1dd979c7..c77be821 100644
--- a/R/gg-miss-var.R
+++ b/R/gg-miss-var.R
@@ -12,7 +12,7 @@
 #'
 #' @return a ggplot object depicting the number of missings in a given column
 #'
-#' @seealso [geom_miss_point()] [gg_miss_case()] [gg_miss_case_cumsum] [gg_miss_fct()] [gg_miss_span()] [gg_miss_var()] [gg_miss_var_cumsum()] [gg_miss_which()]
+#' @seealso [geom_miss_point()] [gg_miss_case()] [gg_miss_case_cumsum()] [gg_miss_fct()] [gg_miss_span()] [gg_miss_var()] [gg_miss_var_cumsum()] [gg_miss_which()]
 #'
 #' @export
 #'
diff --git a/R/gg-miss-which.R b/R/gg-miss-which.R
index 75608aef..07bd9145 100644
--- a/R/gg-miss-which.R
+++ b/R/gg-miss-which.R
@@ -9,7 +9,7 @@
 #'
 #' @return a ggplot object of which variables contains missing values
 #'
-#' @seealso [geom_miss_point()] [gg_miss_case()] [gg_miss_case_cumsum] [gg_miss_fct()] [gg_miss_span()] [gg_miss_var()] [gg_miss_var_cumsum()] [gg_miss_which()]
+#' @seealso [geom_miss_point()] [gg_miss_case()] [gg_miss_case_cumsum()] [gg_miss_fct()] [gg_miss_span()] [gg_miss_var()] [gg_miss_var_cumsum()] [gg_miss_which()]
 #'
 #' @export
 #'
diff --git a/_pkgdown.yml b/_pkgdown.yml
index ba42be6f..d9073324 100644
--- a/_pkgdown.yml
+++ b/_pkgdown.yml
@@ -8,7 +8,7 @@ home:
   - text: Learn more
     href: https://github.com/njtierney/naniar
 authors:
-  Nick Tierney:
+  Nicholas Tierney:
     href: https://njtierney.com/
   Di Cook:
     href: https://www.dicook.org/
diff --git a/man/geom_miss_point.Rd b/man/geom_miss_point.Rd
index fdf1153f..f92941af 100644
--- a/man/geom_miss_point.Rd
+++ b/man/geom_miss_point.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/geom-miss-point.R
 \name{geom_miss_point}
 \alias{geom_miss_point}
-\title{geom_miss_point}
+\title{Plot Missing Data Points}
 \usage{
 geom_miss_point(
   mapping = NULL,
@@ -67,11 +67,8 @@ values in ggplot2. To do so it uses methods from ggobi to display missing
 data points 10\\% below the minimum value, so that the values can be seen on
 the same axis.
 }
-\details{
-Plot Missing Data Points
-}
 \note{
-Warning message if na.rm = T is supplied.
+Warning message if \code{na.rm = T} is supplied.
 }
 \examples{
 \dontrun{
@@ -99,5 +96,6 @@ ggplot(airquality,
 }
 }
 \seealso{
-[gg_miss_case()][gg_miss_case_cumsum()][gg_miss_fct()][gg_miss_span()][gg_miss_var()][gg_miss_var_cumsum()][gg_miss_which()]
+\code{\link[=gg_miss_case]{gg_miss_case()}} \code{\link[=gg_miss_case_cumsum]{gg_miss_case_cumsum()}} \code{\link[=gg_miss_fct]{gg_miss_fct()}}
+\code{\link[=gg_miss_span]{gg_miss_span()}} \code{\link[=gg_miss_var]{gg_miss_var()}} \code{\link[=gg_miss_var_cumsum]{gg_miss_var_cumsum()}} \code{\link[=gg_miss_which]{gg_miss_which()}}
 }
diff --git a/man/gg_miss_case.Rd b/man/gg_miss_case.Rd
index aeb90d38..e82d2cdd 100644
--- a/man/gg_miss_case.Rd
+++ b/man/gg_miss_case.Rd
@@ -38,5 +38,5 @@ gg_miss_case(airquality, facet = Month, show_pct = TRUE)
 }
 }
 \seealso{
-\code{\link[=geom_miss_point]{geom_miss_point()}} \link{gg_miss_case_cumsum} \code{\link[=gg_miss_fct]{gg_miss_fct()}} \code{\link[=gg_miss_span]{gg_miss_span()}} \code{\link[=gg_miss_var]{gg_miss_var()}} \code{\link[=gg_miss_var_cumsum]{gg_miss_var_cumsum()}} \code{\link[=gg_miss_which]{gg_miss_which()}}
+\code{\link[=geom_miss_point]{geom_miss_point()}} \code{\link[=gg_miss_case_cumsum]{gg_miss_case_cumsum()}} \code{\link[=gg_miss_fct]{gg_miss_fct()}} \code{\link[=gg_miss_span]{gg_miss_span()}} \code{\link[=gg_miss_var]{gg_miss_var()}} \code{\link[=gg_miss_var_cumsum]{gg_miss_var_cumsum()}} \code{\link[=gg_miss_which]{gg_miss_which()}}
 }
diff --git a/man/gg_miss_fct.Rd b/man/gg_miss_fct.Rd
index 3bd00745..6adc80d5 100644
--- a/man/gg_miss_fct.Rd
+++ b/man/gg_miss_fct.Rd
@@ -30,5 +30,5 @@ gg_miss_fct(x = riskfactors, fct = marital) + labs(title = "NA in Risk Factors a
 
 }
 \seealso{
-\code{\link[=geom_miss_point]{geom_miss_point()}} \code{\link[=gg_miss_case]{gg_miss_case()}} \link{gg_miss_case_cumsum} \code{\link[=gg_miss_span]{gg_miss_span()}} \code{\link[=gg_miss_var]{gg_miss_var()}} \code{\link[=gg_miss_var_cumsum]{gg_miss_var_cumsum()}} \code{\link[=gg_miss_which]{gg_miss_which()}}
+\code{\link[=geom_miss_point]{geom_miss_point()}} \code{\link[=gg_miss_case]{gg_miss_case()}} \code{\link[=gg_miss_case_cumsum]{gg_miss_case_cumsum()}} \code{\link[=gg_miss_span]{gg_miss_span()}} \code{\link[=gg_miss_var]{gg_miss_var()}} \code{\link[=gg_miss_var_cumsum]{gg_miss_var_cumsum()}} \code{\link[=gg_miss_which]{gg_miss_which()}}
 }
diff --git a/man/gg_miss_span.Rd b/man/gg_miss_span.Rd
index d62af96c..26d8e9e3 100644
--- a/man/gg_miss_span.Rd
+++ b/man/gg_miss_span.Rd
@@ -37,5 +37,5 @@ gg_miss_span(pedestrian, hourly_counts, span_every = 3000) + theme_dark()
 }
 }
 \seealso{
-\code{\link[=geom_miss_point]{geom_miss_point()}} \code{\link[=gg_miss_case]{gg_miss_case()}} \link{gg_miss_case_cumsum} \code{\link[=gg_miss_fct]{gg_miss_fct()}} \code{\link[=gg_miss_var]{gg_miss_var()}} \code{\link[=gg_miss_var_cumsum]{gg_miss_var_cumsum()}} \code{\link[=gg_miss_which]{gg_miss_which()}}
+\code{\link[=geom_miss_point]{geom_miss_point()}} \code{\link[=gg_miss_case]{gg_miss_case()}} \code{\link[=gg_miss_case_cumsum]{gg_miss_case_cumsum()}} \code{\link[=gg_miss_fct]{gg_miss_fct()}} \code{\link[=gg_miss_var]{gg_miss_var()}} \code{\link[=gg_miss_var_cumsum]{gg_miss_var_cumsum()}} \code{\link[=gg_miss_which]{gg_miss_which()}}
 }
diff --git a/man/gg_miss_var.Rd b/man/gg_miss_var.Rd
index 6763376a..8d608d6a 100644
--- a/man/gg_miss_var.Rd
+++ b/man/gg_miss_var.Rd
@@ -35,5 +35,5 @@ gg_miss_var(airquality, Month, show_pct = TRUE) + ylim(0, 100)
 }
 }
 \seealso{
-\code{\link[=geom_miss_point]{geom_miss_point()}} \code{\link[=gg_miss_case]{gg_miss_case()}} \link{gg_miss_case_cumsum} \code{\link[=gg_miss_fct]{gg_miss_fct()}} \code{\link[=gg_miss_span]{gg_miss_span()}} \code{\link[=gg_miss_var]{gg_miss_var()}} \code{\link[=gg_miss_var_cumsum]{gg_miss_var_cumsum()}} \code{\link[=gg_miss_which]{gg_miss_which()}}
+\code{\link[=geom_miss_point]{geom_miss_point()}} \code{\link[=gg_miss_case]{gg_miss_case()}} \code{\link[=gg_miss_case_cumsum]{gg_miss_case_cumsum()}} \code{\link[=gg_miss_fct]{gg_miss_fct()}} \code{\link[=gg_miss_span]{gg_miss_span()}} \code{\link[=gg_miss_var]{gg_miss_var()}} \code{\link[=gg_miss_var_cumsum]{gg_miss_var_cumsum()}} \code{\link[=gg_miss_which]{gg_miss_which()}}
 }
diff --git a/man/gg_miss_var_cumsum.Rd b/man/gg_miss_var_cumsum.Rd
index 2735b082..0b91a751 100644
--- a/man/gg_miss_var_cumsum.Rd
+++ b/man/gg_miss_var_cumsum.Rd
@@ -22,5 +22,5 @@ default minimal theme is used, which can be customised as normal for ggplot.
 gg_miss_var_cumsum(airquality)
 }
 \seealso{
-\code{\link[=geom_miss_point]{geom_miss_point()}} \code{\link[=gg_miss_case]{gg_miss_case()}} \link{gg_miss_case_cumsum} \code{\link[=gg_miss_fct]{gg_miss_fct()}} \code{\link[=gg_miss_span]{gg_miss_span()}} \code{\link[=gg_miss_var]{gg_miss_var()}} \code{\link[=gg_miss_which]{gg_miss_which()}}
+\code{\link[=geom_miss_point]{geom_miss_point()}} \code{\link[=gg_miss_case]{gg_miss_case()}} \code{\link[=gg_miss_case_cumsum]{gg_miss_case_cumsum()}} \code{\link[=gg_miss_fct]{gg_miss_fct()}} \code{\link[=gg_miss_span]{gg_miss_span()}} \code{\link[=gg_miss_var]{gg_miss_var()}} \code{\link[=gg_miss_which]{gg_miss_which()}}
 }
diff --git a/man/gg_miss_which.Rd b/man/gg_miss_which.Rd
index 4d81bc8f..3dcda2d1 100644
--- a/man/gg_miss_which.Rd
+++ b/man/gg_miss_which.Rd
@@ -22,5 +22,5 @@ customised as normal for ggplot.
 gg_miss_which(airquality)
 }
 \seealso{
-\code{\link[=geom_miss_point]{geom_miss_point()}} \code{\link[=gg_miss_case]{gg_miss_case()}} \link{gg_miss_case_cumsum} \code{\link[=gg_miss_fct]{gg_miss_fct()}} \code{\link[=gg_miss_span]{gg_miss_span()}} \code{\link[=gg_miss_var]{gg_miss_var()}} \code{\link[=gg_miss_var_cumsum]{gg_miss_var_cumsum()}} \code{\link[=gg_miss_which]{gg_miss_which()}}
+\code{\link[=geom_miss_point]{geom_miss_point()}} \code{\link[=gg_miss_case]{gg_miss_case()}} \code{\link[=gg_miss_case_cumsum]{gg_miss_case_cumsum()}} \code{\link[=gg_miss_fct]{gg_miss_fct()}} \code{\link[=gg_miss_span]{gg_miss_span()}} \code{\link[=gg_miss_var]{gg_miss_var()}} \code{\link[=gg_miss_var_cumsum]{gg_miss_var_cumsum()}} \code{\link[=gg_miss_which]{gg_miss_which()}}
 }

From c6144a19e3541ce2d7ddb0d6518d20eb68554c3c Mon Sep 17 00:00:00 2001
From: olivroy <olivierroy71@hotmail.com>
Date: Fri, 15 Mar 2024 12:27:54 -0400
Subject: [PATCH 9/9] Use more the defaults in package docs + move reexports to
 a single file

---
 R/naniar-package.R | 17 ++++-------------
 R/utils.R          |  4 ++++
 man/naniar.Rd      | 10 ++++++++--
 man/reexports.Rd   |  4 ++--
 4 files changed, 18 insertions(+), 17 deletions(-)

diff --git a/R/naniar-package.R b/R/naniar-package.R
index b94286c1..49b4c9dd 100644
--- a/R/naniar-package.R
+++ b/R/naniar-package.R
@@ -1,26 +1,17 @@
-#' naniar
-#'
+#' @description
 #' naniar is a package to make it easier to summarise and handle missing values
 #' in R. It strives to do this in a way that is as consistent with tidyverse
 #' principles as possible.  The work is fully discussed at Tierney & Cook (2023)
 #' <doi:10.18637/jss.v105.i07>.
 #'
 #' @name naniar
-#' @docType package
-#' @seealso [add_any_miss()] [add_label_missings()] [add_label_shadow()] [add_miss_cluster()] [add_n_miss()] [add_prop_miss()] [add_shadow()] [add_shadow_shift()] [as_shadow()] [bind_shadow()] [cast_shadow()] [cast_shadow_shift()] [cast_shadow_shift_label()] [draw_key_missing_point()] [gather_shadow()] [geom_miss_point()] [gg_miss_case()] [gg_miss_case_cumsum()] [gg_miss_fct()] [gg_miss_span()] [gg_miss_var()] [gg_miss_var_cumsum()] [gg_miss_which()] [label_miss_1d()] [label_miss_2d()] [label_missings()] [pct_miss_case()] [prop_miss_case()] [pct_miss_var()] [prop_miss_var()] [pct_complete_case()] [prop_complete_case()] [pct_complete_var()] [prop_complete_var()] [miss_prop_summary()] [miss_case_summary()] [miss_case_table()] [miss_summary()] [miss_var_prop()] [miss_var_run()] [miss_var_span()] [miss_var_summary()] [miss_var_table()] [n_complete()] [n_complete_row()] [n_miss()] [n_miss_row()] [pct_complete()] [pct_miss()] [prop_complete()] [prop_complete_row()] [prop_miss()] [prop_miss_row()] [replace_to_na()] [replace_with_na()] [replace_with_na_all()] [replace_with_na_at()] [replace_with_na_if()] [shadow_shift()] [stat_miss_point()] [vis_miss()] [where_na()]
 "_PACKAGE"
 
-#' @import ggplot2
-#' @import rlang
-NULL
-
-#' @importFrom stats median
-#' @importFrom visdat vis_miss
-#' @export
-visdat::vis_miss
-
 ## usethis namespace: start
 #' @importFrom lifecycle deprecated
+#' @import ggplot2
+#' @importFrom stats median
+#' @import rlang
 ## usethis namespace: end
 NULL
 
diff --git a/R/utils.R b/R/utils.R
index ff195851..9805d4af 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -10,6 +10,10 @@ rlang::is_na
 #' @export
 rlang::are_na
 
+#' @importFrom visdat vis_miss
+#' @export
+visdat::vis_miss
+
 #' Group By Helper
 #'
 #' This is a wrapper to facilitate the `grouped_df` S3 method.
diff --git a/man/naniar.Rd b/man/naniar.Rd
index 329c5f88..b94577da 100644
--- a/man/naniar.Rd
+++ b/man/naniar.Rd
@@ -4,7 +4,7 @@
 \name{naniar}
 \alias{naniar-package}
 \alias{naniar}
-\title{naniar}
+\title{naniar: Data Structures, Summaries, and Visualisations for Missing Data}
 \description{
 naniar is a package to make it easier to summarise and handle missing values
 in R. It strives to do this in a way that is as consistent with tidyverse
@@ -12,7 +12,13 @@ principles as possible.  The work is fully discussed at Tierney & Cook (2023)
 \url{doi:10.18637/jss.v105.i07}.
 }
 \seealso{
-\code{\link[=add_any_miss]{add_any_miss()}} \code{\link[=add_label_missings]{add_label_missings()}} \code{\link[=add_label_shadow]{add_label_shadow()}} \code{\link[=add_miss_cluster]{add_miss_cluster()}} \code{\link[=add_n_miss]{add_n_miss()}} \code{\link[=add_prop_miss]{add_prop_miss()}} \code{\link[=add_shadow]{add_shadow()}} \code{\link[=add_shadow_shift]{add_shadow_shift()}} \code{\link[=as_shadow]{as_shadow()}} \code{\link[=bind_shadow]{bind_shadow()}} \code{\link[=cast_shadow]{cast_shadow()}} \code{\link[=cast_shadow_shift]{cast_shadow_shift()}} \code{\link[=cast_shadow_shift_label]{cast_shadow_shift_label()}} \code{\link[=draw_key_missing_point]{draw_key_missing_point()}} \code{\link[=gather_shadow]{gather_shadow()}} \code{\link[=geom_miss_point]{geom_miss_point()}} \code{\link[=gg_miss_case]{gg_miss_case()}} \code{\link[=gg_miss_case_cumsum]{gg_miss_case_cumsum()}} \code{\link[=gg_miss_fct]{gg_miss_fct()}} \code{\link[=gg_miss_span]{gg_miss_span()}} \code{\link[=gg_miss_var]{gg_miss_var()}} \code{\link[=gg_miss_var_cumsum]{gg_miss_var_cumsum()}} \code{\link[=gg_miss_which]{gg_miss_which()}} \code{\link[=label_miss_1d]{label_miss_1d()}} \code{\link[=label_miss_2d]{label_miss_2d()}} \code{\link[=label_missings]{label_missings()}} \code{\link[=pct_miss_case]{pct_miss_case()}} \code{\link[=prop_miss_case]{prop_miss_case()}} \code{\link[=pct_miss_var]{pct_miss_var()}} \code{\link[=prop_miss_var]{prop_miss_var()}} \code{\link[=pct_complete_case]{pct_complete_case()}} \code{\link[=prop_complete_case]{prop_complete_case()}} \code{\link[=pct_complete_var]{pct_complete_var()}} \code{\link[=prop_complete_var]{prop_complete_var()}} \code{\link[=miss_prop_summary]{miss_prop_summary()}} \code{\link[=miss_case_summary]{miss_case_summary()}} \code{\link[=miss_case_table]{miss_case_table()}} \code{\link[=miss_summary]{miss_summary()}} \code{\link[=miss_var_prop]{miss_var_prop()}} \code{\link[=miss_var_run]{miss_var_run()}} \code{\link[=miss_var_span]{miss_var_span()}} \code{\link[=miss_var_summary]{miss_var_summary()}} \code{\link[=miss_var_table]{miss_var_table()}} \code{\link[=n_complete]{n_complete()}} \code{\link[=n_complete_row]{n_complete_row()}} \code{\link[=n_miss]{n_miss()}} \code{\link[=n_miss_row]{n_miss_row()}} \code{\link[=pct_complete]{pct_complete()}} \code{\link[=pct_miss]{pct_miss()}} \code{\link[=prop_complete]{prop_complete()}} \code{\link[=prop_complete_row]{prop_complete_row()}} \code{\link[=prop_miss]{prop_miss()}} \code{\link[=prop_miss_row]{prop_miss_row()}} \code{\link[=replace_to_na]{replace_to_na()}} \code{\link[=replace_with_na]{replace_with_na()}} \code{\link[=replace_with_na_all]{replace_with_na_all()}} \code{\link[=replace_with_na_at]{replace_with_na_at()}} \code{\link[=replace_with_na_if]{replace_with_na_if()}} \code{\link[=shadow_shift]{shadow_shift()}} \code{\link[=stat_miss_point]{stat_miss_point()}} \code{\link[=vis_miss]{vis_miss()}} \code{\link[=where_na]{where_na()}}
+Useful links:
+\itemize{
+  \item \url{https://github.com/njtierney/naniar}
+  \item \url{https://naniar.njtierney.com/}
+  \item Report bugs at \url{https://github.com/njtierney/naniar/issues}
+}
+
 }
 \author{
 \strong{Maintainer}: Nicholas Tierney \email{nicholas.tierney@gmail.com} (\href{https://orcid.org/0000-0003-1460-8722}{ORCID})
diff --git a/man/reexports.Rd b/man/reexports.Rd
index 938e9db2..c2e3846e 100644
--- a/man/reexports.Rd
+++ b/man/reexports.Rd
@@ -1,12 +1,12 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/naniar-package.R, R/utils.R
+% Please edit documentation in R/utils.R
 \docType{import}
 \name{reexports}
 \alias{reexports}
-\alias{vis_miss}
 \alias{\%>\%}
 \alias{is_na}
 \alias{are_na}
+\alias{vis_miss}
 \title{Objects exported from other packages}
 \keyword{internal}
 \description{