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    <title>R-Ladies Chicago on R-Ladies Chicago</title>
    <link>/</link>
    <description>Recent content in R-Ladies Chicago on R-Ladies Chicago</description>
    <generator>Hugo -- gohugo.io</generator>
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    <copyright>&amp;copy; 2018</copyright>
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    <item>
      <title>An Antarctic Tour of the Tidyverse</title>
      <link>/talk/2020-08-31-meetup/</link>
      <pubDate>Tue, 25 Aug 2020 00:00:00 -0500</pubDate>
      
      <guid>/talk/2020-08-31-meetup/</guid>
      <description>

&lt;h2 id=&#34;about&#34;&gt;About&lt;/h2&gt;

&lt;p&gt;&amp;lsquo;
Learn how to explore and manipulate data in R with packages from the Tidyverse. We&amp;rsquo;ll introduce the 8 core packages (&lt;a href=&#34;https://www.tidyverse.org/packages/&#34; target=&#34;_blank&#34;&gt;https://www.tidyverse.org/packages/&lt;/a&gt;) that make up the Tidyverse and use at least one function from each package while exploring a dataset on the migration of penguins.&lt;/p&gt;

&lt;p&gt;Information about the Speaker:&lt;/p&gt;

&lt;p&gt;Dr. Silvia Canelón is a postdoctoral research scientist in biomedical informatics at the University of Pennsylvania in Philadelphia. She uses data science in the public and population health fields and is particularly interested in leveraging electronic health record data to study reproductive health outcomes. Silvia is formally trained as a biomedical engineer and holds her bachelor’s degree from the University of Minnesota and her doctoral degree from Purdue University. She loves community organizing and is currently pursuing the RStudio Instructor Certification as a way to help build power in her communities. Website: &lt;a href=&#34;https://silvia.rbind.io/&#34; target=&#34;_blank&#34;&gt;https://silvia.rbind.io/&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;Location:
Zoom link will be emailed a day before the event.&lt;/p&gt;

&lt;h2 id=&#34;prerequisites&#34;&gt;Prerequisites:&lt;/h2&gt;

&lt;p&gt;We ask that R-Ladies who are interested in this event please sign up for a free R Studio Cloud account. This will be the easiest route to follow along with the workshop.&lt;/p&gt;

&lt;ul&gt;
&lt;li&gt;&lt;a href=&#34;https://rstudio.cloud/&#34; target=&#34;_blank&#34;&gt;https://rstudio.cloud/&lt;/a&gt;&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;You can also follow along on your own computer as well. Note that help will be limited if you run into issues.&lt;/p&gt;

&lt;p&gt;Install the following if you would rather follow along on your local computer.:&lt;/p&gt;

&lt;ul&gt;
&lt;li&gt;&lt;p&gt;R:
&lt;a href=&#34;https://www.r-project.org/&#34; target=&#34;_blank&#34;&gt;https://www.r-project.org/&lt;/a&gt;&lt;/p&gt;&lt;/li&gt;

&lt;li&gt;&lt;p&gt;R Studio:
&lt;a href=&#34;https://rstudio.com/products/rstudio/download/&#34; target=&#34;_blank&#34;&gt;https://rstudio.com/products/rstudio/download/&lt;/a&gt;&lt;/p&gt;&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;Skill Level:
None. All levels are welcomed.&lt;/p&gt;

&lt;h2 id=&#34;schedule&#34;&gt;Schedule&lt;/h2&gt;

&lt;p&gt;5:30 - 6:00 &amp;ndash; Networking and Technical help
6:10 - 6:20 &amp;ndash; Announcements and Introduction
6:30 - 7:35 &amp;ndash; Dr. Silvia Canelón: An Antarctic Tour of the Tidyverse
7:35 - 7:45 &amp;ndash; QAs and Goodbyes&lt;/p&gt;

&lt;p&gt;##FAQ&lt;/p&gt;

&lt;p&gt;Q: Are men welcome to attend this event?
A: Our primary mission is to encourage more women and non-binary individuals to get involved in the R community. &lt;strong&gt;&lt;em&gt;As such, we strongly encourage that all men who attend this event have a female or non-binary sponsor. Please contact [masked] if you have questions.&lt;/em&gt;&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;Additionally, please help us by spreading the word about R-Ladies, and by being respectful of the fact that this event is primarily for women/non-binary/female-identifying individuals.&lt;/p&gt;

&lt;h2 id=&#34;what-to-bring&#34;&gt;What to bring&lt;/h2&gt;

&lt;p&gt;Yourself/friends! And a laptop - this will be an interactive event.&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Please note:&lt;/strong&gt;&lt;br /&gt;
Our primary mission is to encourage more women and non-binary individuals to get involved in the R community. &lt;em&gt;As such, we strongly encourage that all men who attend this event have a female or non-binary sponsor, as spots may be limited. Please contact chicago@rladies.org if you have questions.&lt;/em&gt;&lt;/p&gt;

&lt;p&gt;Be sure to RSVP on &lt;a href=&#34;https://www.meetup.com/rladies-chicago/events/269010701/&#34; target=&#34;_blank&#34;&gt;Meetup&lt;/a&gt;&lt;/p&gt;
</description>
    </item>
    
    <item>
      <title>R-Ladies Book Club</title>
      <link>/post/2020_05_11_book_club/</link>
      <pubDate>Mon, 11 May 2020 21:13:14 -0500</pubDate>
      
      <guid>/post/2020_05_11_book_club/</guid>
      <description>


&lt;p&gt;Come beat those quarentine blues! Outside of the huge number of tools and packages in R, we can continue to expand our knowledge of the statistical engine behind these. We will particularly focus on developing starter questions for data analysis projects.
You can sign up &lt;a href=&#34;https://bit.ly/3b125El&#34;&gt;here&lt;/a&gt;.&lt;/p&gt;
</description>
    </item>
    
    <item>
      <title>Introducing our 2020 Career Series!</title>
      <link>/post/2020-02-07-career-series/</link>
      <pubDate>Fri, 07 Feb 2020 21:13:14 -0500</pubDate>
      
      <guid>/post/2020-02-07-career-series/</guid>
      <description>


&lt;p&gt;R-Ladies Chicago is proud to host our three-part Career Series in February, March, and April. With hiring season on the horizon, our Career Series will empower R-Ladies with the skills necessary to succeed in the data field. Join us for any/all of these events!&lt;/p&gt;
&lt;p&gt;Thank you to Groupon for hosting! All events will take place at &lt;a href=&#34;https://goo.gl/maps/BoaBY8Gn9fKDgqTBA&#34;&gt;Groupon Corporate Headquarters&lt;/a&gt; (600 W. Chicago Avenue; Chicago, IL 60654).&lt;/p&gt;
&lt;p&gt;&lt;em&gt;Please check in at the front desk then go up to the third floor&lt;/em&gt;&lt;/p&gt;
&lt;hr /&gt;
&lt;div id=&#34;part-i-using-r-to-land-the-job-a-resume-building-tutorial&#34; class=&#34;section level2&#34;&gt;
&lt;h2&gt;Part I: Using R to Land the Job: A Resume Building Tutorial&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Wednesday, February 26 at 6pm&lt;/strong&gt;&lt;br /&gt;
&lt;strong&gt;&lt;a href=&#34;https://www.meetup.com/rladies-chicago/events/268252477/&#34;&gt;RSVP on Meetup&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;To kick off our Career Series, our co-organizer Scarlett Winters will lead a tutorial on how to build your resume using the pagedown R package. This tutorial will equip you with the tools to revamp your resume and prove to employers you know how to code in R well before your interview!&lt;/p&gt;
&lt;hr /&gt;
&lt;/div&gt;
&lt;div id=&#34;part-ii-our-best-resource-is-each-other-a-qa-panel-on-developing-your-network-and-learning-from-one-another&#34; class=&#34;section level2&#34;&gt;
&lt;h2&gt;Part II: Our Best Resource is Each Other: A Q&amp;amp;A Panel on Developing Your Network and Learning from One Another&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Wednesday, March 18 at 6pm&lt;/strong&gt;&lt;br /&gt;
&lt;strong&gt;&lt;a href=&#34;https://www.meetup.com/rladies-chicago/events/269010701/&#34;&gt;RSVP on Meetup&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;Next in the Career Series line-up, we will host a career Q&amp;amp;A panel featuring three data scientists from academia, industry, and the experimentation side. This will be a great opportunity to develop your network and gain valuable insights from data scientists across industries.&lt;/p&gt;
&lt;div class=&#34;figure&#34;&gt;
&lt;img src=&#34;https://secure.meetupstatic.com/photos/event/b/7/5/8/highres_489346936.jpeg&#34; alt=&#34;Career Development Panelists&#34; /&gt;
&lt;p class=&#34;caption&#34;&gt;Career Development Panelists&lt;/p&gt;
&lt;/div&gt;
&lt;hr /&gt;
&lt;/div&gt;
&lt;div id=&#34;part-iii-keep-growing-building-and-maintaining-your-online-presence&#34; class=&#34;section level2&#34;&gt;
&lt;h2&gt;Part III: Keep Growing: Building and Maintaining Your Online Presence&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Wednesday, April 22 at 6pm&lt;/strong&gt;&lt;br /&gt;
&lt;em&gt;Meetup Link coming soon&lt;/em&gt;&lt;/p&gt;
&lt;p&gt;The final installment of our Career Series will be a talk on how to build and maintain your online presence in the data space. Have you ever read someone’s data science blog or Twitter and wondered how they can juggle it all? Find out how they do it, and how you can, too! We’ll learn what makes a strong online presence and how you can build and maintain yours.&lt;/p&gt;
&lt;hr /&gt;
&lt;p&gt;&lt;em&gt;Please note&lt;/em&gt;: Event details are subject to change! Please check our &lt;a href=&#34;https://www.meetup.com/rladies-chicago&#34;&gt;Meetup Page&lt;/a&gt; for the most up-to-date information on this series.&lt;/p&gt;
&lt;/div&gt;
</description>
    </item>
    
    <item>
      <title>R-Ladies Wine Preferences: Sip and Code Recap and Tutorial</title>
      <link>/post/2019_07_01_block/</link>
      <pubDate>Wed, 03 Jul 2019 00:00:00 +0000</pubDate>
      
      <guid>/post/2019_07_01_block/</guid>
      <description>


&lt;p&gt;Last Wednesday, June 26, 2019, the R-Ladies Chicago got together for a Summer Social Meetup over wine and coding. It was a great opportunity to meet people, socialize and, of course, have some drinks!&lt;/p&gt;
&lt;p&gt;We were supposed to taste some beverages (wine tasting was optional, there were non-alcoholic drinks too) and rate them for a collaborative activity afterwards. So, what are the R-Ladies wine preferences? In this post I’ll present the data we produced in a simple tutorial.&lt;/p&gt;
&lt;p&gt;For this activity I just used tidyverse to do some data wrangling and visualization, RCurl to upload the csv from the R-Ladies Github repository and lubridate to play a little bit with the Timestamp variable.&lt;/p&gt;
&lt;p&gt;Let’s see how the data set looks like:&lt;/p&gt;
&lt;pre class=&#34;r&#34;&gt;&lt;code&gt;#uploading packages
library(tidyverse)
library(lubridate) 
library(RCurl)

#uploading data from the R-Ladies repository (Here I&amp;#39;m using RCurl)
wine&amp;lt;-read.csv(text=getURL(&amp;quot;https://raw.githubusercontent.com/rladies-chicago/2019-06-26-sip-and-code-round2/master/sipncode2019.csv&amp;quot;))

#taking a look at the first lines
head(wine)&lt;/code&gt;&lt;/pre&gt;
&lt;pre&gt;&lt;code&gt;##       Timestamp drink_category                drink_name drink_rating
## 1 6/26/19 18:02  Non-Alcoholic Blood Orange Pellegrino&amp;#39;s           84
## 2 6/26/19 18:03  Non-Alcoholic Blood Orange Pellegrino&amp;#39;s           85
## 3 6/26/19 18:04  Non-Alcoholic Blood Orange Pellegrino&amp;#39;s           88
## 4 6/26/19 18:10  Non-Alcoholic        Grapefruit LaCroix           90
## 5 6/26/19 18:10  Non-Alcoholic        Grapefruit LaCroix           80
## 6 6/26/19 18:11  Non-Alcoholic Blood Orange Pellegrino&amp;#39;s           98&lt;/code&gt;&lt;/pre&gt;
&lt;p&gt;We have four variables: 1) Timestamp, that is a factor with the time that the rate was entered in the data set; 2) drink_category categorizes the beverages as non-alcoholic or as Wine/Champagne; 3) drink_name, that is a factor; 4) drink_rating, an interger. Let’s see how many ratings each drink category received.&lt;/p&gt;
&lt;pre class=&#34;r&#34;&gt;&lt;code&gt;wine%&amp;gt;%
  count(drink_category)&lt;/code&gt;&lt;/pre&gt;
&lt;pre&gt;&lt;code&gt;## # A tibble: 2 x 2
##   drink_category     n
##   &amp;lt;fct&amp;gt;          &amp;lt;int&amp;gt;
## 1 Non-Alcoholic     19
## 2 Wine/Champagne    70&lt;/code&gt;&lt;/pre&gt;
&lt;p&gt;The data set has 89 ratings, 19 for non-alcoholic and 70 for alcoholic beverages. I’ll focus this exploration on the alcoholic drinks. All the bottles were opened at the same time and we were free to choose whatever we wanted to try. It means that each participant had tried as many wines as they wanted, but rated each of them only once. Let’s take a look at the distribution of these ratings among our options.&lt;/p&gt;
&lt;pre class=&#34;r&#34;&gt;&lt;code&gt;#setting the ggplot theme
theme_set(theme_classic())

#plotting
wine%&amp;gt;%
  filter(drink_category==&amp;quot;Wine/Champagne&amp;quot;)%&amp;gt;%
  ggplot(aes(drink_name,drink_rating))+
  geom_boxplot()+
  geom_dotplot(binaxis=&amp;quot;y&amp;quot;,
               stackdir=&amp;quot;center&amp;quot;,
               dotsize = .8,
               fill=&amp;quot;red&amp;quot;)+
  theme(axis.text.x = element_text(angle=70, vjust=0.6))+
  labs(title=&amp;quot;Distribution of ratings per alcoholic beverages&amp;quot;,
        caption=&amp;quot;Source: R-Ladies Chicago&amp;quot;,
        x=&amp;quot;&amp;quot;,
        y=&amp;quot;Ratings&amp;quot;)&lt;/code&gt;&lt;/pre&gt;
&lt;p&gt;&lt;img src=&#34;/post/2019_07_01_Block_files/figure-html/unnamed-chunk-3-1.png&#34; width=&#34;672&#34; /&gt;&lt;/p&gt;
&lt;p&gt;The red dots are each rating in the data set. The data is very unequally distributed and this can lead us to biased conclusions if we don’t analyze them carefully. For example, the Chardonnay - Kendall Jackson has the highest mean rate (89.5), but only two participants tasted it. In turn, Rose (La Vie Ferme) was tasted by 14 ladies and presented a lower mean rate (87).&lt;/p&gt;
&lt;p&gt;So, I decided to reclassify the drinks in other three broader categories: 1) White Wine/Champagne, where I’ve put the Champagne - Brut, all the Chardonnays and the Sauvignon Blanc; 2) Light Red Wine, which are the Pinot Noir and Rose; 3) Red Wine, that are the Garnacha, Malbec and Red Blend. Then, I’ve plotted the distribution of the ratings in this new classification.&lt;/p&gt;
&lt;pre class=&#34;r&#34;&gt;&lt;code&gt;#reclassifying 

wine_new&amp;lt;-wine%&amp;gt;%
  filter(drink_category==&amp;quot;Wine/Champagne&amp;quot;)%&amp;gt;%
  mutate(new_category=as.factor(case_when(drink_name==&amp;quot;Chardonnay - La Crema&amp;quot; ~ &amp;quot;Champagne/White Wine&amp;quot;,
                                          drink_name==&amp;quot;Chardonnay - Cambria&amp;quot; ~ &amp;quot;Champagne/White Wine&amp;quot;,
                                          drink_name==&amp;quot;Pinot Noir&amp;quot; ~ &amp;quot;Light Red Wine&amp;quot;,
                                          drink_name==&amp;quot;Garnacha (Vina Zorzal)&amp;quot; ~ &amp;quot;Red Wine&amp;quot;,
                                          drink_name==&amp;quot;Malbec&amp;quot; ~ &amp;quot;Red Wine&amp;quot;,
                                          drink_name==&amp;quot;Champagne - Brut&amp;quot; ~ &amp;quot;Champagne/White Wine&amp;quot;,
                                          drink_name== &amp;quot;Red Blend&amp;quot; ~ &amp;quot;Red Wine&amp;quot;,
                                          drink_name== &amp;quot;Sauvignon Blanc&amp;quot; ~ &amp;quot;Champagne/White Wine&amp;quot;,
                                          drink_name==&amp;quot;Chardonnay&amp;quot; ~ &amp;quot;Champagne/White Wine&amp;quot;,
                                          drink_name==&amp;quot;Rose (La Vieille Ferme)&amp;quot; ~ &amp;quot;Light Red Wine&amp;quot;,
                                          drink_name==&amp;quot;Chardonnay - Butter&amp;quot; ~ &amp;quot;Champagne/White Wine&amp;quot;,
                                          drink_name==&amp;quot;Chardonnay - Kendall Jackson&amp;quot; ~ &amp;quot;Champagne/White Wine&amp;quot;)))

#plotting

wine_new%&amp;gt;%
  ggplot(aes(new_category,drink_rating))+
  geom_boxplot()+
  geom_dotplot(binaxis=&amp;quot;y&amp;quot;,
               stackdir=&amp;quot;center&amp;quot;,
               dotsize = .8,
               fill=&amp;quot;red&amp;quot;)+
  theme(axis.text.x = element_text(angle=45, vjust=0.6))+
  labs(title=&amp;quot;Distribution of ratings per category&amp;quot;,
       caption=&amp;quot;Source: R-Ladies Chicago&amp;quot;,
       x=&amp;quot;&amp;quot;,
       y=&amp;quot;Ratings&amp;quot;)&lt;/code&gt;&lt;/pre&gt;
&lt;p&gt;&lt;img src=&#34;/post/2019_07_01_Block_files/figure-html/unnamed-chunk-4-1.png&#34; width=&#34;672&#34; /&gt;&lt;/p&gt;
&lt;p&gt;If we look only at the mean of the ratings (Light Red Wine= 86.3; Champagne/White Wine= 85.8; Red Wine= 84.9) it seems that R-Ladies slightly prefered the Light Red Wines. However, there are some many outliers in all three categories that is hard to say if there was any preferred type.&lt;/p&gt;
&lt;p&gt;The data set comprises ratings along one hour of the meeting, from around 6 to 7 pm. The meeting started at 5:45 and finished around 8 or 8:30 pm. The next plot shows how the ratings were distributed in this time frame.&lt;/p&gt;
&lt;pre class=&#34;r&#34;&gt;&lt;code&gt;##transforming the time variable using lubridate  
wine_new$Timestamp&amp;lt;-mdy_hm(wine_new$Timestamp)


#ploting the count of alcoholic beverages tasted every 3 minutes
wine_new%&amp;gt;%
  ggplot(aes(Timestamp))+
  geom_freqpoly(binwidth= 180)+
  labs(title=&amp;quot;Count of alcoholic beverages tasted&amp;quot;,
       subtitle=&amp;quot;at every three minutes&amp;quot;,
       caption=&amp;quot;Source: R-Ladies Chicago&amp;quot;,
       x= &amp;quot;&amp;quot;)&lt;/code&gt;&lt;/pre&gt;
&lt;p&gt;&lt;img src=&#34;/post/2019_07_01_Block_files/figure-html/unnamed-chunk-5-1.png&#34; width=&#34;672&#34; /&gt;&lt;/p&gt;
&lt;p&gt;This plot makes sense to me. People started to arrive in bigger numbers around 6pm and we were encouraged to start tasting the wines by the R-Ladies board by 6:15. Around 6:30 there was a general announcement about how to scan the bar code in order to rate the beverages. These may explain the higher numbers of ratings around 6:15 and 6:40. By 6:45 we had annoucenments and intros, what explains the lower count of ratings around this time.&lt;/p&gt;
&lt;p&gt;So, what can we say about the R-Ladies wine preferences? Probably that a good wine is the one you drink with inspiring women while playing a bit with ggplot.&lt;/p&gt;
&lt;p&gt;If you are new to R and got a bit lost in this tutorial I highly recommend to take a look at the R-Ladies Chicago &lt;a href=&#34;https://github.com/rladies-chicago/beginners-r&#34;&gt;Beginners’ Repository&lt;/a&gt; on Github.&lt;/p&gt;
&lt;div id=&#34;about-the-author&#34; class=&#34;section level4&#34;&gt;
&lt;h4&gt;About the Author:&lt;/h4&gt;
&lt;p&gt;&lt;a href=&#34;https://www.linkedin.com/in/nataliablock/&#34;&gt;Natalia Block&lt;/a&gt; is a Research and Data Analyst. She has worked with R on research projects for political organizations, campaigns and in academia. When not coding, she is drawing (and vice-versa).&lt;/p&gt;
&lt;/div&gt;
</description>
    </item>
    
    <item>
      <title>Join Us!</title>
      <link>/project/join/</link>
      <pubDate>Sat, 18 May 2019 00:00:00 -0500</pubDate>
      
      <guid>/project/join/</guid>
      <description>&lt;p&gt;R-Ladies is a worldwide organization that  promotes gender diversity in the R community via meetups and mentorship in a friendly and safe environment.&lt;/p&gt;

&lt;p&gt;Join our Slack community at this link: &lt;a href=&#34;https://rladiesinvite.herokuapp.com/&#34; target=&#34;_blank&#34;&gt;https://rladiesinvite.herokuapp.com/&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;Follow our Meetup age and join us at our in-person events: &lt;a href=&#34;https://www.meetup.com/rladies-chicago/&#34; target=&#34;_blank&#34;&gt;https://www.meetup.com/rladies-chicago/&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;We are always looking for fellow R-Ladies who are interested in giving a talk, suggesting a Meetup topic, leading a study group, or writing a &lt;a href=&#34;https://github.com/rladies-chicago/blog&#34; target=&#34;_blank&#34;&gt;blog post&lt;/a&gt;. Please reach out!&lt;/p&gt;

&lt;p&gt;&lt;img src=&#34;/img/join_us.png&#34; align=&#34;center&#34; style=&#34;margin: 5px 10px&#34; alt=&#34;&#34;&gt;&lt;/p&gt;

&lt;p&gt;&lt;/p&gt;

&lt;p&gt;All are welcome to our events. However, our primary mission is to encourage more women and non-binary individuals to get involved in the R community.  &lt;em&gt;As such, we strongly encourage that all men who attend our events have a female or non-binary sponsor. Please contact chicago@rladies.org if you have questions.&lt;/em&gt;&lt;/p&gt;
</description>
    </item>
    
    <item>
      <title>Support Us!</title>
      <link>/project/support/</link>
      <pubDate>Sat, 18 May 2019 00:00:00 -0500</pubDate>
      
      <guid>/project/support/</guid>
      <description>&lt;p&gt;We are always looking for organizations to support our monthly Meetups! Specifically, we look for companies or organizations that can host us in their space and/or provide food and drink for Meetup attendees.&lt;/p&gt;

&lt;p&gt;If you are interested in potentially hosting R-Ladies, please fill out this &lt;a href=&#34;https://forms.gle/RP9KqV3x7QpymjgE7&#34; target=&#34;_blank&#34;&gt;Google Form&lt;/a&gt;. Also, please read our &lt;strong&gt;&lt;a href=&#34;https://docs.google.com/document/d/1NhsM6x1HHaoxXAIYXmApc2lWDQqMTkLQaWuPOoQsaBM/edit?usp=sharing&#34; target=&#34;_blank&#34;&gt;Sponsor Space Requirements &amp;amp; Guidelines&lt;/a&gt;&lt;/strong&gt; for details about what a host space needs.&lt;/p&gt;

&lt;p&gt;&lt;/p&gt;

&lt;p&gt;&lt;img src=&#34;/img/rladies_sponsors_v2.jpg&#34; alt=&#34;We are grateful to our sponsors for their essential contributions to R-Ladies Chicago&#34; /&gt;&lt;/p&gt;
</description>
    </item>
    
    <item>
      <title> R Forwards Package Workshop Recap</title>
      <link>/post/2019-02-28-rworkshop_recap/</link>
      <pubDate>Tue, 26 Feb 2019 00:00:00 +0000</pubDate>
      
      <guid>/post/2019-02-28-rworkshop_recap/</guid>
      <description>


&lt;p&gt;Last Saturday, February 23, 2019, took place the R Forwards Women’s Package Workshop in Chicago at Center for Spatial Data Science, where Angela Li (&lt;a href=&#34;https://twitter.com/CivicAngela&#34;&gt;CivicAngela&lt;/a&gt;) and Stephanie Kirmer (&lt;a href=&#34;https://twitter.com/data_stephanie&#34;&gt;data_stephanie&lt;/a&gt;) conducted the workshop. 40 R-Ladies attended from different parts of the Chicago area to increase their abilities with R.&lt;/p&gt;
&lt;div class=&#34;figure&#34;&gt;
&lt;img src=&#34;https://pbs.twimg.com/media/D0HzZViWkAAv-za.jpg&#34; alt=&#34;Image Caption: Women’s Package Development Workshop Attendees&#34; /&gt;
&lt;p class=&#34;caption&#34;&gt;&lt;em&gt;Image Caption: Women’s Package Development Workshop Attendees&lt;/em&gt;&lt;/p&gt;
&lt;/div&gt;
&lt;div id=&#34;what-do-we-learn&#34; class=&#34;section level2&#34;&gt;
&lt;h2&gt;What do we learn?&lt;/h2&gt;
&lt;p&gt;We learned about packages, which are the fundamental units of reproducible R code. Also, we worked on how to create our package, the documentation associated and how to include a unit test to the process.&lt;/p&gt;
&lt;p&gt;We saw a variety of subjects in a friendly and collaborative environment. This course was very hands on, and both instructors solved many questions, or for the person sitting next to you. Both Angela and Stephanie presented each subject, and after that, we learned by doing simple exercises about the matter, and if eventually, you can not have any idea about how to continue you can ask for help about how to solve the problem. Just keep going and keep learning.&lt;/p&gt;
&lt;div id=&#34;material-for-this-workshop&#34; class=&#34;section level3&#34;&gt;
&lt;h3&gt;Material for this workshop&lt;/h3&gt;
&lt;p&gt;You can find all the material of the course in this link: &lt;a href=&#34;https://github.com/forwards/workshops/tree/master/Chicago2019&#34;&gt;Chicago 2019 Forwards Workshop&lt;/a&gt;.&lt;/p&gt;
&lt;p&gt;Allow me to introduce the 5 decks presented during the workshop:&lt;/p&gt;
&lt;/div&gt;
&lt;/div&gt;
&lt;div id=&#34;first-deck-package-development&#34; class=&#34;section level2&#34;&gt;
&lt;h2&gt;First Deck: Package Development&lt;/h2&gt;
&lt;p&gt;Check the presentation &lt;a href=&#34;https://docs.google.com/presentation/d/1DhOqaIumkwzbdglnyugoe53f63pFkQdQwgIdZpmEOok/edit#slide=id.p4&#34;&gt;here&lt;/a&gt;:&lt;/p&gt;
&lt;p&gt;This presentation is about R packages, Angela suggested to check how many R packages have already installed on our computer (you can’t believe the numbers :) ), the most common sources for R packages (Cran and Github), and an explanation of the difference (and similarities) between developing a package and developing a script.&lt;/p&gt;
&lt;div id=&#34;takeaways&#34; class=&#34;section level4&#34;&gt;
&lt;h4&gt;Takeaways:&lt;/h4&gt;
&lt;ul&gt;
&lt;li&gt;A review for R package from the theory&lt;br /&gt;
&lt;/li&gt;
&lt;li&gt;Use of several commands like: &lt;code&gt;R.home()&lt;/code&gt;, &lt;code&gt;list.files(R.home())&lt;/code&gt;, &lt;code&gt;R.version&lt;/code&gt;&lt;/li&gt;
&lt;/ul&gt;
&lt;/div&gt;
&lt;/div&gt;
&lt;div id=&#34;second-deck-packages-r-code&#34; class=&#34;section level2&#34;&gt;
&lt;h2&gt;Second Deck: Packages &amp;amp; R Code&lt;/h2&gt;
&lt;p&gt;During this second part, Angela revisited the definition of a package. Also, she analyzed the reasons to use RStudio projects. After this introduction, we started with the process of building a simple package.&lt;/p&gt;
&lt;p&gt;Later Stephanie took over explaining what git and GitHub are, and also she spent a moment speaking about version control, ending this second part making a project in RStudio from our repo.&lt;/p&gt;
&lt;p&gt;Check the presentation &lt;a href=&#34;https://docs.google.com/presentation/d/1zFSArrDtVKNKvu5ZNZ6E4v64f-P7xy8x4-9c4c_B_cY/edit#slide=id.p1&#34;&gt;here&lt;/a&gt;&lt;/p&gt;
&lt;div id=&#34;takeaways-1&#34; class=&#34;section level4&#34;&gt;
&lt;h4&gt;Takeaways:&lt;/h4&gt;
&lt;ul&gt;
&lt;li&gt;We learned more about the package &lt;a href=&#34;https://github.com/r-lib/usethis&#34;&gt;usethis&lt;/a&gt; (for example &lt;code&gt;usethis::create_package(&amp;quot;~/Desktop/mypackage&amp;quot;)&lt;/code&gt;)&lt;br /&gt;
&lt;/li&gt;
&lt;li&gt;How to create our first package&lt;br /&gt;
&lt;/li&gt;
&lt;li&gt;How to make a project in RStudio from our repo&lt;br /&gt;
&lt;/li&gt;
&lt;li&gt;Useful resource: &lt;a href=&#34;https://happygitwithr.com&#34;&gt;Happy Git with R&lt;/a&gt;&lt;br /&gt;
&lt;/li&gt;
&lt;li&gt;Useful resource II: &lt;a href=&#34;https://peerj.com/preprints/3159/&#34;&gt;Excuse me, do you have a moment to talk about version control?&lt;/a&gt;&lt;/li&gt;
&lt;/ul&gt;
&lt;/div&gt;
&lt;/div&gt;
&lt;div id=&#34;third-deck-unit-test&#34; class=&#34;section level2&#34;&gt;
&lt;h2&gt;Third Deck: Unit Test&lt;/h2&gt;
&lt;p&gt;During this third part, we reviewed the reason-why is a great idea to use unit test: because it is an excellent way to be sure that our functionalities continue working after each change.&lt;br /&gt;
We also tested the coverage for our package. As a final recommendation, we should include checking our work as a regular part of the iterative process to develop a package (or in any development).&lt;/p&gt;
&lt;p&gt;Check the presentation &lt;a href=&#34;https://docs.google.com/presentation/d/1-UfFgts0RXOw8VOtEvGv3iMC8rcI7g2QDRhL1MJFk6A/edit#slide=id.p1&#34;&gt;here&lt;/a&gt;:&lt;/p&gt;
&lt;div id=&#34;takeaways-2&#34; class=&#34;section level4&#34;&gt;
&lt;h4&gt;Takeaways:&lt;/h4&gt;
&lt;ul&gt;
&lt;li&gt;Theory and practice about how to include unit test in your code&lt;br /&gt;
&lt;/li&gt;
&lt;li&gt;Useful resource: &lt;a href=&#34;http://r-pkgs.had.co.nz/tests.html&#34;&gt;Testing&lt;/a&gt;&lt;/li&gt;
&lt;/ul&gt;
&lt;/div&gt;
&lt;/div&gt;
&lt;div id=&#34;fourth-deck-documentation&#34; class=&#34;section level2&#34;&gt;
&lt;h2&gt;Fourth Deck: Documentation&lt;/h2&gt;
&lt;p&gt;During this fourth part, Stephanie spoke about documentation and why it is always a good idea to include it in your development process: because documentation is the way to preserve the information about the tools. She reviews Markdown and Roxygen, and also we opened up some function in R to check the Roxygen header and read the documentation, later we included a header in some of the functions created along the workshop. Also, we used Vignettes, Read.me and news to explain how our packages work.&lt;/p&gt;
&lt;p&gt;Check the presentation: &lt;a href=&#34;https://docs.google.com/presentation/d/1f_uW09RVRF-Bu0kkVCHtB9OYYWxSjngtxcZ8ZvTquSU/edit#slide=id.p1&#34;&gt;here&lt;/a&gt;&lt;/p&gt;
&lt;div id=&#34;takeaways-3&#34; class=&#34;section level4&#34;&gt;
&lt;h4&gt;Takeaways:&lt;/h4&gt;
&lt;ul&gt;
&lt;li&gt;How to document &lt;a href=&#34;http://r-pkgs.had.co.nz/data.html#documenting-data&#34;&gt;data objects&lt;/a&gt;&lt;br /&gt;
&lt;/li&gt;
&lt;li&gt;How to document &lt;a href=&#34;http://r-pkgs.had.co.nz/man.html#man-classes&#34;&gt;classes and methods objects&lt;/a&gt;&lt;br /&gt;
&lt;/li&gt;
&lt;li&gt;How to document &lt;a href=&#34;http://r-pkgs.had.co.nz/man.html#man-packages&#34;&gt;packages objects&lt;/a&gt;&lt;br /&gt;
&lt;/li&gt;
&lt;li&gt;Information about &lt;a href=&#34;http://r-pkgs.had.co.nz/vignettes.html&#34;&gt;Vignettes&lt;/a&gt;&lt;/li&gt;
&lt;/ul&gt;
&lt;/div&gt;
&lt;/div&gt;
&lt;div id=&#34;fifth-deck-share&#34; class=&#34;section level2&#34;&gt;
&lt;h2&gt;Fifth Deck: Share&lt;/h2&gt;
&lt;p&gt;During this fifth part, we revisited the concept of licenses and the three main open source licenses (CC0, MIT, and GPL). We learned how to use helper to set up the type of license. We got about dependencies and the three types of dependencies (imports, suggests, and depends). We also saw how to access functions in imported packages. We spoke about the reasons to use depends instead on imports. Another concept presented was Automated checking to run automated checks for common problems in R packages. Moreover, also we saw something about how to make a submission to CRAN.&lt;/p&gt;
&lt;p&gt;Check the presentation: &lt;a href=&#34;https://docs.google.com/presentation/d/17kkDKmcR8BiEo-5aoOkVHcfmOzqp87dR8gy3BwygkD4/edit#slide=id.p1&#34;&gt;here&lt;/a&gt;&lt;/p&gt;
&lt;div id=&#34;takeaways-4&#34; class=&#34;section level4&#34;&gt;
&lt;h4&gt;Takeaways:&lt;/h4&gt;
&lt;ul&gt;
&lt;li&gt;&lt;a href=&#34;http://r-pkgs.had.co.nz/check.html&#34;&gt;Automated Checking&lt;/a&gt;&lt;/li&gt;
&lt;/ul&gt;
&lt;/div&gt;
&lt;/div&gt;
&lt;div id=&#34;additional-materials&#34; class=&#34;section level2&#34;&gt;
&lt;h2&gt;Additional Materials:&lt;/h2&gt;
&lt;p&gt;There are a lot of resources to continue digging into all the concept presented, some of them are:&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;&lt;a href=&#34;https://adv-r.hadley.nz&#34;&gt;Advanced R&lt;/a&gt;&lt;br /&gt;
&lt;/li&gt;
&lt;li&gt;&lt;a href=&#34;http://r-pkgs.had.co.nz&#34;&gt;R packages&lt;/a&gt;&lt;br /&gt;
&lt;/li&gt;
&lt;li&gt;&lt;a href=&#34;https://r4ds.had.co.nz&#34;&gt;R for data science&lt;/a&gt;&lt;/li&gt;
&lt;/ul&gt;
&lt;div id=&#34;about-the-author&#34; class=&#34;section level3&#34;&gt;
&lt;h3&gt;About the Author:&lt;/h3&gt;
&lt;p&gt;&lt;strong&gt;Florencia Mangini&lt;/strong&gt; is a software engineer interested in using data to make a positive impact on society. She enjoys learning and using R, with a focus on data visualization and data mining. She loves to write about business analytics, project management and data science in her blog: &lt;a href=&#34;http://www.thinkingondata.com/&#34;&gt;www.thinkingondata.com&lt;/a&gt;.&lt;/p&gt;
&lt;/div&gt;
&lt;/div&gt;
</description>
    </item>
    
    <item>
      <title>January Meetup Recap: What We Learned at rstudio::conf</title>
      <link>/post/2019-02-04-jan-recap/</link>
      <pubDate>Mon, 04 Feb 2019 21:13:14 -0500</pubDate>
      
      <guid>/post/2019-02-04-jan-recap/</guid>
      <description>


&lt;p&gt;For our &lt;a href=&#34;https://www.meetup.com/rladies-chicago/events/257346957/&#34;&gt;January R-Ladies Chicago Meetup&lt;/a&gt;, five Chicago R-Ladies presented lightning talks on topics they learned about at rstudio::conf 2019. Three of our organizers attended workshops on diversity scholarships, so we were especially excited to hear what they learned. Natalie Jorion also volunteered to speak, and we ended up having a total of five speakers! Each person spoke for 10 minutes on a subject they thought was interesting.&lt;/p&gt;
&lt;p&gt;Topics of the night included deep learning, improving data project organization, tips for Shiny applications, reproducible research, and contributing to open source.&lt;/p&gt;
&lt;p&gt;First, &lt;a href=&#34;https://twitter.com/ckwill36&#34;&gt;Caroline Williams&lt;/a&gt; told us what she learned at the deep learning in R workshop. Her slides can be found &lt;a href=&#34;https://docs.google.com/presentation/d/1HZBv5TmzP6oQkZthnmw3GfK1fN1TYQjM-F11qvoFQgo/edit#slide=id.p&#34;&gt;here&lt;/a&gt;.&lt;/p&gt;
&lt;blockquote class=&#34;twitter-tweet&#34; data-lang=&#34;en&#34;&gt;
&lt;p lang=&#34;en&#34; dir=&#34;ltr&#34;&gt;
Our &lt;a href=&#34;https://twitter.com/hashtag/rstudioconf?src=hash&amp;amp;ref_src=twsrc%5Etfw&#34;&gt;#rstudioconf&lt;/a&gt; lighting talks are starting with &lt;a href=&#34;https://twitter.com/ckwill36?ref_src=twsrc%5Etfw&#34;&gt;&lt;span class=&#34;citation&#34;&gt;@ckwill36&lt;/span&gt;&lt;/a&gt; discussing deep learning &lt;a href=&#34;https://t.co/Z85sg0IT2p&#34;&gt;pic.twitter.com/Z85sg0IT2p&lt;/a&gt;
&lt;/p&gt;
— R-Ladies Chicago (&lt;span class=&#34;citation&#34;&gt;@RLadiesChicago&lt;/span&gt;) &lt;a href=&#34;https://twitter.com/RLadiesChicago/status/1090046174252462080?ref_src=twsrc%5Etfw&#34;&gt;January 29, 2019&lt;/a&gt;
&lt;/blockquote&gt;
&lt;script async src=&#34;https://platform.twitter.com/widgets.js&#34; charset=&#34;utf-8&#34;&gt;&lt;/script&gt;
&lt;p&gt;Next, &lt;a href=&#34;https://twitter.com/ayanalytics&#34;&gt;Amy Yang&lt;/a&gt; explained how to properly write file paths in R. Her slides can be found &lt;a href=&#34;https://docs.google.com/presentation/d/1c7sNVqVByTia57IhK1Uux6zrVrbpnWJuLT9LAFf2uh4/&#34;&gt;here&lt;/a&gt;.&lt;/p&gt;
&lt;blockquote class=&#34;twitter-tweet&#34; data-lang=&#34;en&#34;&gt;
&lt;p lang=&#34;en&#34; dir=&#34;ltr&#34;&gt;
.&lt;a href=&#34;https://twitter.com/ayanalytics?ref_src=twsrc%5Etfw&#34;&gt;&lt;span class=&#34;citation&#34;&gt;@ayanalytics&lt;/span&gt;&lt;/a&gt; relaying &lt;a href=&#34;https://twitter.com/JennyBryan?ref_src=twsrc%5Etfw&#34;&gt;&lt;span class=&#34;citation&#34;&gt;@JennyBryan&lt;/span&gt;&lt;/a&gt;’s legendary advice about file paths to &lt;a href=&#34;https://twitter.com/hashtag/RLadies?src=hash&amp;amp;ref_src=twsrc%5Etfw&#34;&gt;#RLadies&lt;/a&gt; Chicago. &lt;a href=&#34;https://twitter.com/hashtag/rstudioconf?src=hash&amp;amp;ref_src=twsrc%5Etfw&#34;&gt;#rstudioconf&lt;/a&gt; ⚡️talks &lt;a href=&#34;https://t.co/jh4mJknTCW&#34;&gt;pic.twitter.com/jh4mJknTCW&lt;/a&gt;
&lt;/p&gt;
— R-Ladies Chicago (&lt;span class=&#34;citation&#34;&gt;@RLadiesChicago&lt;/span&gt;) &lt;a href=&#34;https://twitter.com/RLadiesChicago/status/1090050001148018689?ref_src=twsrc%5Etfw&#34;&gt;January 29, 2019&lt;/a&gt;
&lt;/blockquote&gt;
&lt;script async src=&#34;https://platform.twitter.com/widgets.js&#34; charset=&#34;utf-8&#34;&gt;&lt;/script&gt;
&lt;p&gt;After that, &lt;a href=&#34;https://www.linkedin.com/in/njorion/&#34;&gt;Natalie Jorion&lt;/a&gt; gave us 10 tips for making better Shiny apps. Her slides can be found &lt;a href=&#34;https://docs.google.com/presentation/d/1CD0PMnWAcjau7fzIcXDooiIdjpvDQCCqXr0edkySwxk/edit&#34;&gt;here&lt;/a&gt;.&lt;/p&gt;
&lt;blockquote class=&#34;twitter-tweet&#34; data-lang=&#34;en&#34;&gt;
&lt;p lang=&#34;en&#34; dir=&#34;ltr&#34;&gt;
Natalie Jorion gives us some protips for Shiny apps! &lt;a href=&#34;https://twitter.com/hashtag/RLadies?src=hash&amp;amp;ref_src=twsrc%5Etfw&#34;&gt;#RLadies&lt;/a&gt; &lt;a href=&#34;https://twitter.com/hashtag/RStudioConf?src=hash&amp;amp;ref_src=twsrc%5Etfw&#34;&gt;#RStudioConf&lt;/a&gt; ⚡️talks &lt;a href=&#34;https://t.co/gKyr3qx6vY&#34;&gt;pic.twitter.com/gKyr3qx6vY&lt;/a&gt;
&lt;/p&gt;
— R-Ladies Chicago (&lt;span class=&#34;citation&#34;&gt;@RLadiesChicago&lt;/span&gt;) &lt;a href=&#34;https://twitter.com/RLadiesChicago/status/1090052135536992259?ref_src=twsrc%5Etfw&#34;&gt;January 29, 2019&lt;/a&gt;
&lt;/blockquote&gt;
&lt;script async src=&#34;https://platform.twitter.com/widgets.js&#34; charset=&#34;utf-8&#34;&gt;&lt;/script&gt;
&lt;p&gt;Following that, &lt;a href=&#34;https://katherinesimeon.github.io/&#34;&gt;Katherine Simeon&lt;/a&gt; presented on what she learned about conducting reproducible research in R. Her (&lt;a href=&#34;https://bookdown.org/yihui/rmarkdown/xaringan.html&#34;&gt;xaringan!&lt;/a&gt;) slides can be found &lt;a href=&#34;https://katherinesimeon.github.io/20190128-reproducible-research/#1&#34;&gt;here&lt;/a&gt;.&lt;/p&gt;
&lt;blockquote class=&#34;twitter-tweet&#34; data-lang=&#34;en&#34;&gt;
&lt;p lang=&#34;en&#34; dir=&#34;ltr&#34;&gt;
New packages introduced by &lt;a href=&#34;https://twitter.com/kitkatbar429?ref_src=twsrc%5Etfw&#34;&gt;&lt;span class=&#34;citation&#34;&gt;@kitkatbar429&lt;/span&gt;&lt;/a&gt; in her reproducible research talk following up &lt;a href=&#34;https://twitter.com/hashtag/rstudioconf?src=hash&amp;amp;ref_src=twsrc%5Etfw&#34;&gt;#rstudioconf&lt;/a&gt; include: usethis, rrtools, containerit, and “Knit with Parameters” in &lt;a href=&#34;https://twitter.com/hashtag/rmarkdown?src=hash&amp;amp;ref_src=twsrc%5Etfw&#34;&gt;#rmarkdown&lt;/a&gt; &lt;a href=&#34;https://t.co/rg1PMlXbDi&#34;&gt;pic.twitter.com/rg1PMlXbDi&lt;/a&gt;
&lt;/p&gt;
— R-Ladies Chicago (&lt;span class=&#34;citation&#34;&gt;@RLadiesChicago&lt;/span&gt;) &lt;a href=&#34;https://twitter.com/RLadiesChicago/status/1090056012718059520?ref_src=twsrc%5Etfw&#34;&gt;January 29, 2019&lt;/a&gt;
&lt;/blockquote&gt;
&lt;script async src=&#34;https://platform.twitter.com/widgets.js&#34; charset=&#34;utf-8&#34;&gt;&lt;/script&gt;
&lt;p&gt;Finally, I talked about my experience contributing to open source at Tidyverse Developer Day. My slides can be found &lt;a href=&#34;https://docs.google.com/presentation/d/1iodn7rsklI1wryld-NN_Dslr7tHM0xyoMx2C3RRFTJc/&#34;&gt;here&lt;/a&gt;.&lt;/p&gt;
&lt;blockquote class=&#34;twitter-tweet&#34; data-lang=&#34;en&#34;&gt;
&lt;p lang=&#34;en&#34; dir=&#34;ltr&#34;&gt;
.&lt;a href=&#34;https://twitter.com/CivicAngela?ref_src=twsrc%5Etfw&#34;&gt;&lt;span class=&#34;citation&#34;&gt;@CivicAngela&lt;/span&gt;&lt;/a&gt; tells us about submitting a pull request during &lt;a href=&#34;https://twitter.com/hashtag/TidyverseDevDay?src=hash&amp;amp;ref_src=twsrc%5Etfw&#34;&gt;#TidyverseDevDay&lt;/a&gt;. 💪🏼 &lt;a href=&#34;https://twitter.com/hashtag/RLadies?src=hash&amp;amp;ref_src=twsrc%5Etfw&#34;&gt;#RLadies&lt;/a&gt; &lt;a href=&#34;https://t.co/uttH5w3rlY&#34;&gt;pic.twitter.com/uttH5w3rlY&lt;/a&gt;
&lt;/p&gt;
— R-Ladies Chicago (&lt;span class=&#34;citation&#34;&gt;@RLadiesChicago&lt;/span&gt;) &lt;a href=&#34;https://twitter.com/RLadiesChicago/status/1090058635508633602?ref_src=twsrc%5Etfw&#34;&gt;January 29, 2019&lt;/a&gt;
&lt;/blockquote&gt;
&lt;script async src=&#34;https://platform.twitter.com/widgets.js&#34; charset=&#34;utf-8&#34;&gt;&lt;/script&gt;
&lt;p&gt;I thought the lightning talk format where each person spoke for 5-10 minutes was a nice way to cover many different topics at once, and I was impressed at how many people braved the sub-zero weather and the snow to come to the Meetup! Thank you &lt;a href=&#34;https://www.wework.com/buildings/20-w-kinzie-st--chicago--IL&#34;&gt;WeWork Kinzie&lt;/a&gt; for hosting us and keeping us warm at the Meetup, and &lt;a href=&#34;https://developer.microsoft.com/en-us/advocates/index.html&#34;&gt;Microsoft&lt;/a&gt; for food as always.&lt;/p&gt;
&lt;div id=&#34;additional-reading&#34; class=&#34;section level2&#34;&gt;
&lt;h2&gt;Additional Reading&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;&lt;p&gt;&lt;a href=&#34;https://twitter.com/manginiflor&#34;&gt;Florencia Mangini&lt;/a&gt; put together a lovely detailed recap of the event with more links to things we mentioned in our presentations, which you can read at &lt;a href=&#34;http://www.thinkingondata.com/r-ladies-chicago-what-we-learned-at-rstudioconf-2019-lightning-talks/&#34;&gt;her blog&lt;/a&gt;!&lt;/p&gt;&lt;/li&gt;
&lt;li&gt;&lt;p&gt;Organizer &lt;a href=&#34;http://amazingspecialist.coolcatscoding.com/&#34;&gt;Ola Giwa&lt;/a&gt; wrote a blog post on her experience at rstudio::conf &lt;a href=&#34;https://medium.com/@zaynaibg/rstudio-conf-8768c9b07345&#34;&gt;here&lt;/a&gt;.&lt;/p&gt;&lt;/li&gt;
&lt;/ul&gt;
&lt;/div&gt;
</description>
    </item>
    
    <item>
      <title>Introducing Chicago Schools Enrollment Data to R</title>
      <link>/post/2019-01-21-mack/</link>
      <pubDate>Thu, 24 Jan 2019 00:00:00 +0000</pubDate>
      
      <guid>/post/2019-01-21-mack/</guid>
      <description>
&lt;script src=&#34;/rmarkdown-libs/htmlwidgets/htmlwidgets.js&#34;&gt;&lt;/script&gt;
&lt;script src=&#34;/rmarkdown-libs/plotly-binding/plotly.js&#34;&gt;&lt;/script&gt;
&lt;script src=&#34;/rmarkdown-libs/typedarray/typedarray.min.js&#34;&gt;&lt;/script&gt;
&lt;script src=&#34;/rmarkdown-libs/jquery/jquery.min.js&#34;&gt;&lt;/script&gt;
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&lt;script src=&#34;/rmarkdown-libs/plotly-main/plotly-latest.min.js&#34;&gt;&lt;/script&gt;


&lt;p&gt;The City of Chicago and Chicago Public Schools (CPS) have made data on annual enrollments, school locations, and other school features available to the public. After a bit of wrangling (frankly maybe more than just a bit) these data can be used in R to get key visualizations.&lt;/p&gt;
&lt;p&gt;My own interest in the schools data began with a desire to understand more about the spread of charter schools in the city, and also more about the sharp enrollment declines that some regular public high schools have experienced since the early ’00s. Putting together the annual enrollment data provided by the CPS into a longitudinal form gave some insights into both questions. In addition, the City provides a shapefile of school locations as of the 2014-2015 school year that has enough information to make a first pass at seeing the expansion of schools of other-than-regular governance. In this post I’ll share those illustrations.&lt;/p&gt;
&lt;pre class=&#34;r&#34;&gt;&lt;code&gt;library(tidyverse)
library(lubridate)&lt;/code&gt;&lt;/pre&gt;
&lt;p&gt;The &lt;a href=&#34;https://github.com/cymack/CPSenrollment&#34;&gt;all-high school enrollment data.frame&lt;/a&gt; is available at my github site in &lt;a href=&#34;https://github.com/cymack/CPSenrollment/blob/master/enrollment_all_hs.csv&#34;&gt;csv&lt;/a&gt; and &lt;a href=&#34;https://github.com/cymack/CPSenrollment/blob/master/enrollment_all_hs.Rds&#34;&gt;Rds&lt;/a&gt; formats. In the command below we use RCurl::getURL to get the csv version directly from the raw files at github.&lt;/p&gt;
&lt;pre class=&#34;r&#34;&gt;&lt;code&gt;# The enrollment data#
require(&amp;quot;RCurl&amp;quot;)
library(RCurl)

enrollment_all_hs &amp;lt;-read.csv(text=getURL(&amp;quot;https://raw.githubusercontent.com/cymack/CPSenrollment/master/enrollment_all_hs.csv&amp;quot;)) &lt;/code&gt;&lt;/pre&gt;
&lt;p&gt;For most years, school governance, as I’ve called it, has only two levels, “regular” and “charter.” In 2016 a third level appears for the first time, “contract.” As there were only 4 contract high schools in that year, I’ve collapsed that factor with charter to create “charter etc.” Then I extracted a table of annual counts of regular and charter etc schools, and plotted a graph.&lt;/p&gt;
&lt;pre class=&#34;r&#34;&gt;&lt;code&gt;tbl.allschools_years_gov &amp;lt;- 
  enrollment_all_hs %&amp;gt;% 
  dplyr::mutate(govern = forcats::as_factor(govern)) %&amp;gt;% 
  dplyr::mutate(govern = forcats::fct_collapse(govern, &amp;quot;charter etc&amp;quot; = c(&amp;quot;charter&amp;quot;, &amp;quot;other&amp;quot;))) %&amp;gt;%
  dplyr::group_by(year, govern) %&amp;gt;% 
  dplyr::count()

# tbl.allschools_years_gov %&amp;gt;% print(n=24)
    
# So in any table or graph derived from this frame, the &amp;quot;charter etc&amp;quot; factor includes
# contract or other schools that in the main data frame are factored separately
# as &amp;quot;other.&amp;quot;&lt;/code&gt;&lt;/pre&gt;
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&lt;p&gt;So the visual evidence from this graph is that the number of charter and other schools of non-standard governance types has increased over the period, and that this increase has been the main dynamic in the number of high schools under CPS jurisdiction, since the number of regular schools has oscillated in a more steady manner. Though there is some up-and-downness, the share of non-standard schools has increased significantly.&lt;/p&gt;
&lt;p&gt;We can get another perspective on the growth of the number of charter institutions by mapping school locations at different time points. The City of Chicago has, among numerous data files at its &lt;a href=&#34;https://data.cityofchicago.org/&#34;&gt;data hub site&lt;/a&gt;, a shapefile of &lt;a href=&#34;https://data.cityofchicago.org/Education/Chicago-Public-Schools-School-Locations-SY1415/3fhj-xtn5&#34;&gt;school locations in the year 2014-2015&lt;/a&gt;. After some manipulations I’ve come up with spatial data.frames in sf (simple features) format for schools appearing in the enrollment_all_hs frame and the location frame, for the each of the years &lt;a href=&#34;https://github.com/cymack/CPSenrollment/blob/master/school_loc_merged.2006.Rds&#34;&gt;2006-2007&lt;/a&gt; and &lt;a href=&#34;https://github.com/cymack/CPSenrollment/blob/master/school_loc_merged.2016.Rds&#34;&gt;2016-2017&lt;/a&gt;, available on my github site at the links. Again RCurl::getURL in the code chunk is aimed at the raw github files. It is hoped that in the first pass visualization the noise occasioned by mixing data across three years be overwhelmed by strength of the main effect.&lt;/p&gt;
&lt;p&gt;&lt;img src=&#34;/post/2019-01-21-MACK_files/figure-html/maps-1.png&#34; width=&#34;672&#34; style=&#34;display: block; margin: auto auto auto 0;&#34; /&gt;&lt;/p&gt;
&lt;p&gt;Another caveat is that the school types in the maps are derived from the locations data provided by the City of Chicago, and appears to be a different categorization from that in the CPS enrollment data set. The difference seems to affect mostly the charter and other options school types. In this case combining the charter and all other types into one factor level might actually have helped.&lt;/p&gt;
&lt;p&gt;Clearly visible in the maps is the increase in number of high schools overall from 2006 to 2016. The increased density of locations is especially noticeable in the central area of the city, roughly to the west of downtown.&lt;/p&gt;
&lt;div id=&#34;about-the-author&#34; class=&#34;section level4&#34;&gt;
&lt;h4&gt;About the Author:&lt;/h4&gt;
&lt;p&gt;Charlotte Mack is a former economist who is interested in the use of R and other open source data platforms with public data as part of civic activities. She also enjoys black-and-white movies and television, and has recently added new tango to her numerous musical enthusiasms.&lt;/p&gt;
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&lt;p&gt;&lt;a href=&#34;https://github.com/cymack&#34;&gt;cymack&lt;/a&gt;&lt;/p&gt;
&lt;/div&gt;
</description>
    </item>
    
    <item>
      <title>Trying out R Tours</title>
      <link>/post/2018-09-rtours/</link>
      <pubDate>Thu, 27 Sep 2018 21:13:14 -0500</pubDate>
      
      <guid>/post/2018-09-rtours/</guid>
      <description>


&lt;p&gt;At R-Ladies, we want everyone to feel welcome, especially women and minority genders. Our favorite part of R-Ladies is cultivating an inclusive learning community–it is a challenge, but well worth it. As an R Community, where we are passionate about what we do in R, accessibility and inclusivity also means cultivating a welcoming environment for R users of all levels–from beginner to expert to everyone in between.&lt;/p&gt;
&lt;p&gt;The Chicago organizing team works hard to plan our events intentionally where there is a combination of tutorials, talks about specific topics, and social events that showcase the strengths and address the interests of the local R-Ladies community. Some of these events will be better for beginners than others, but we hope that people will join us regardless of their R proficiency. We also hope our members will give us feedback on what they want to learn about in the future. In order to make our meetups more accessible, regardless of the topic, we’ll be piloting a new initiative: &lt;strong&gt;R Tours&lt;/strong&gt;! R Tours will be a 15-minute orientation on R essentials that immediately precede
in person meetups.&lt;/p&gt;
&lt;div id=&#34;why-tours&#34; class=&#34;section level2&#34;&gt;
&lt;h2&gt;Why Tours?&lt;/h2&gt;
&lt;p&gt;At a couple events this past summer, a number of attendees said they had never even seen RStudio before or had just downloaded R on their computer before coming to the meetup. The purpose of R Tours is to provide a super-quick overview to complete beginners before (ideally, each) meetup. Somethings we are considering when developing this initiative:&lt;/p&gt;
&lt;ol style=&#34;list-style-type: decimal&#34;&gt;
&lt;li&gt;&lt;p&gt;What do beginners need to get the most out of that day’s meetup? We’ll open RStudio and introduce each window. We’ll install and load any packages that are necessary for the talk. The goal is for beginners to know where to look when someone live codes. We also don’t want them to be discouraged from following along on their own computers because they had trouble installing things.&lt;/p&gt;&lt;/li&gt;
&lt;li&gt;&lt;p&gt;This isn’t an in-depth tutorial or class that will provide all the information one needs. Also, we want attendees to download the script and run with it. So we used base R with no other packages or files necessary (other than what might be necessary for that day’s meetup). However, we will point attendees to resources where they can learn more about R!&lt;/p&gt;&lt;/li&gt;
&lt;li&gt;&lt;p&gt;We hope that this will be a sustainable, recurring activity that we can do before every meetup to help beginners get more out of each meetup. We also hope it will facilitate community building within our R-Ladies Chapter, where other R-Ladies members can lead this 15-minute tour. It is a great opportunity to contribute to R-Ladies while practicing R teaching skills (and it’s not a big time commitment either!).&lt;/p&gt;&lt;/li&gt;
&lt;/ol&gt;
&lt;p&gt;We’re including a draft of what our R tour might consist of. Check out this &lt;a href=&#34;https://github.com/rladies-chicago/beginners-r&#34;&gt;repo&lt;/a&gt;, where we’ll be updating our R tour for each meetup. This is still a work-in-progress and feedback is greatly appreciated! :)&lt;/p&gt;
&lt;/div&gt;
&lt;div id=&#34;an-example-of-an-r-tour&#34; class=&#34;section level2&#34;&gt;
&lt;h2&gt;An Example of an R Tour&lt;/h2&gt;
&lt;pre class=&#34;r&#34;&gt;&lt;code&gt;### R-Ladies Chicago R TOUR

# Load Data into workspace. Here, we&amp;#39;re loading a sample dataset that is already in R
data(&amp;quot;iris&amp;quot;) 

# See the first six rows of the dataset
head(iris) 

# See how large the dataset is
dim(iris) # output shows number of rows then number of columns

# What is this dataset about? You can use ? for other functions to get more info
?iris 

# See a subset of your data
# Show data where petal length is greater than 2 cm
subset(iris,iris$Petal.Length &amp;gt; 2)

# Save the data as a file in your working directory
write.csv(iris,file=&amp;quot;my_iris_data.csv&amp;quot;) 

# Read a file into R from your working directory
my_iris_data &amp;lt;- read.csv(&amp;quot;my_iris_data.csv&amp;quot;) 
&lt;/code&gt;&lt;/pre&gt;
&lt;/div&gt;
</description>
    </item>
    
    <item>
      <title>Data Viz Study Group Meeting</title>
      <link>/talk/2018-09-10_dataviz/</link>
      <pubDate>Sun, 26 Aug 2018 00:00:00 -0500</pubDate>
      
      <guid>/talk/2018-09-10_dataviz/</guid>
      <description>&lt;p&gt;Join the Data Viz study group for their first meeting!  We&amp;rsquo;ll be exploring the grammar of graphics with R. There will also be an introduction to ggplot2. All are welcome!&lt;/p&gt;

&lt;p&gt;Please email study group coordinator Ola [at] rladies dot org or join our &lt;strong&gt;#sg-dataviz&lt;/strong&gt; slack channel with any questions.&lt;/p&gt;

&lt;p&gt;Please RSVP: &lt;a href=&#34;https://www.meetup.com/rladies-chicago/events/254251305/&#34; target=&#34;_blank&#34;&gt;https://www.meetup.com/rladies-chicago/events/254251305/&lt;/a&gt;&lt;/p&gt;
</description>
    </item>
    
    <item>
      <title>Call for Blog Posts</title>
      <link>/post/2018-07-16_blog_info/</link>
      <pubDate>Mon, 16 Jul 2018 21:13:14 -0500</pubDate>
      
      <guid>/post/2018-07-16_blog_info/</guid>
      <description>


&lt;p&gt;R-Ladies Chicago is excited to start this blog to showcase the perspectives of different members in the R-Ladies Chicago community!&lt;/p&gt;
&lt;p&gt;We are looking for individuals who are interested in contributing to this blog. Whether you just want to write a single blog post or contribute regularly, we want to hear from you!&lt;/p&gt;
&lt;p&gt;We’re hoping to have two new posts each month on this blog. Blog posts could consist of:&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Event Recaps (either an R-Ladies Meetup or Study Group Meeting or another R-related event)&lt;br /&gt;
&lt;/li&gt;
&lt;li&gt;Learning something new in R (introducing a package or function in R)&lt;br /&gt;
&lt;/li&gt;
&lt;li&gt;Member profiles (we would love to spotlight members of the R-Ladies Chicago Community)&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;For more details about contributing, please visit our &lt;a href=&#34;https://github.com/rladies-chicago/blog&#34;&gt;github repo&lt;/a&gt;.&lt;/p&gt;
&lt;p&gt;If you have any questions, please email us at &lt;a href=&#34;mailto:chicago@rladies.org&#34;&gt;chicago@rladies.org&lt;/a&gt;.&lt;/p&gt;
</description>
    </item>
    
    <item>
      <title>Study Groups</title>
      <link>/project/studygroups/</link>
      <pubDate>Wed, 20 Jun 2018 00:00:00 -0500</pubDate>
      
      <guid>/project/studygroups/</guid>
      <description>&lt;p&gt;&lt;img src=&#34;/img/Astrologo.jpg&#34; align=&#34;left&#34; style=&#34;margin: 5px 10px&#34; alt=&#34;&#34;&gt;&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Astrostatistics&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;Astrostatistics is a new emerging field that combines Astrophysics and Statistics. Our Astrostatistics Study Group (ASG) will create opportunities for R people to join the fun in exploring the Universe!&lt;/p&gt;

&lt;p&gt;Visit &lt;a href=&#34;https://asgchicago.github.io/&#34; target=&#34;_blank&#34;&gt;https://asgchicago.github.io/&lt;/a&gt; for more info&lt;/p&gt;

&lt;p&gt;&lt;/p&gt;

&lt;p&gt;&lt;img src=&#34;/img/NLPlogo.jpg&#34; align=&#34;left&#34; style=&#34;margin: 5px 10px&#34; alt=&#34;&#34;&gt;&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Natural Language Processing&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;There are many ways to look at text &amp;amp; language data. The NLP study group explores different aspects of text analysis in the R programming language.&lt;/p&gt;

&lt;p&gt;Visit our github at: &lt;a href=&#34;https://github.com/rladies-nlp&#34; target=&#34;_blank&#34;&gt;https://github.com/rladies-nlp&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Other Study Groups&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;Javascript&lt;br /&gt;
Machine Learning&lt;br /&gt;
GIS/Spatial Data&lt;/p&gt;

&lt;p&gt;Join via &lt;a href=&#34;https://rladiesinvite.herokuapp.com/&#34; target=&#34;_blank&#34;&gt;Slack&lt;/a&gt;!&lt;/p&gt;
</description>
    </item>
    
    <item>
      <title>&#39;Git&#39; down with Git &#43; R (Workshop &amp; Tutorial)</title>
      <link>/talk/2018-11-13-meetup/</link>
      <pubDate>Sun, 01 Jan 2017 00:00:00 -0600</pubDate>
      
      <guid>/talk/2018-11-13-meetup/</guid>
      <description>&lt;p&gt;Learn about using Git &amp;amp; R at our November Meetup! R-Ladies Board Member Ola Giwa will lead a tutorial and workshop to get you up and running with Github and using Git in your workflow. This session will discuss:&lt;/p&gt;

&lt;ul&gt;
&lt;li&gt;Version control and why it is important&lt;br /&gt;&lt;/li&gt;
&lt;li&gt;Fundamental git commands&lt;br /&gt;&lt;/li&gt;
&lt;li&gt;Using Github for collaboration!&lt;br /&gt;
&lt;br /&gt;&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;This event is extremely beginner-friendly! We encourage anyone, regardless of R &amp;amp; Git/Github proficiency, to join us!&lt;/p&gt;

&lt;p&gt;Please RSVP on our &lt;a href=&#34;https://www.meetup.com/rladies-chicago/events/255727048/&#34; target=&#34;_blank&#34;&gt;Meetup page&lt;/a&gt;!&lt;/p&gt;
</description>
    </item>
    
    <item>
      <title>Animation for Effective Data Visualization with R</title>
      <link>/talk/2019-7-24-meetup/</link>
      <pubDate>Sun, 01 Jan 2017 00:00:00 -0600</pubDate>
      
      <guid>/talk/2019-7-24-meetup/</guid>
      <description>&lt;p&gt;Adding animation to graphs can make visualizations eye-catching and effective for transmitting complex information to audiences. In this talk, attendees will learn about using animation in data visualizations in R using ggplot2 and gganimate. Topics will include: how to choose when an animation might (or might not) be an appropriate option for your use case, ways to make sure your visualization still communicates clearly and succinctly when animated, and a hands-on walk-through of how to turn a not-so-great static visualization into a great animated plot. The gganimate package will be the key tool discussed, and some familiarity with ggplot2 is recommended but not required.&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Please note:&lt;/strong&gt;&lt;br /&gt;
Our primary mission is to encourage more women and non-binary individuals to get involved in the R community. &lt;em&gt;As such, we strongly encourage that all men who attend this event have a female or non-binary sponsor. Please contact chicago@rladies.org if you have questions.&lt;/em&gt;&lt;/p&gt;

&lt;p&gt;Please RSVP through &lt;a href=&#34;https://www.meetup.com/rladies-chicago/events/262406111/&#34; target=&#34;_blank&#34;&gt;Meetup&lt;/a&gt;.&lt;/p&gt;
</description>
    </item>
    
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