From 63e0ddbb5698b11a6e28c21f427abdd70ca168c4 Mon Sep 17 00:00:00 2001
From: Carson Sievert <cpsievert1@gmail.com>
Date: Wed, 13 Jul 2016 15:54:58 -0500
Subject: [PATCH] curse you cbind

---
 R/layers2traces.R  |  2 +-
 R/plotly_data.R    |  1 +
 man/plotly_data.Rd | 46 ----------------------------------------------
 3 files changed, 2 insertions(+), 47 deletions(-)

diff --git a/R/layers2traces.R b/R/layers2traces.R
index 3686fc2153..a7a00f2967 100644
--- a/R/layers2traces.R
+++ b/R/layers2traces.R
@@ -645,7 +645,7 @@ ribbon_dat <- function(dat) {
   tmp <- dat[o, ]
   others <- tmp[not_used]
   dat1 <- cbind(x = tmp$x, y = tmp$ymin, others)
-  dat1[n+1, ] <- cbind(x = tmp$x[n], y = tmp$ymin[n], others[n, ])
+  dat1[n+1, ] <- data.frame(x = tmp$x[n], y = tmp$ymin[n], others[n, ])
   # bottom-half of ribbon
   tmp2 <- dat[o2, ]
   others2 <- tmp2[not_used]
diff --git a/R/plotly_data.R b/R/plotly_data.R
index a5abfd757e..929ff0a2ed 100644
--- a/R/plotly_data.R
+++ b/R/plotly_data.R
@@ -8,6 +8,7 @@
 #' @param id a character string or number referencing an "attribute layer".
 #' @return returns a data frame
 #' @examples
+#' @export
 #' 
 #' # use group_by() to define groups of visual markings
 #' p <- txhousing %>%
diff --git a/man/plotly_data.Rd b/man/plotly_data.Rd
index 064ed70362..ebb1e55f83 100644
--- a/man/plotly_data.Rd
+++ b/man/plotly_data.Rd
@@ -19,50 +19,4 @@ returns a data frame
 a plotly visualization (if there are multiple data frames, by default, 
 it returns the most recent one).
 }
-\examples{
-
-# use group_by() to define groups of visual markings
-p <- txhousing \%>\%
-  group_by(city) \%>\%
-  plot_ly(x = ~date, y = ~sales)
-p
-
-# plotly objects preserve data groupings 
-groups(p)
-plotly_data(p)
-
-# dplyr verbs operate on plotly objects as if they were data frames
-p <- economics \%>\%
-  plot_ly(x = ~date, y = ~unemploy / pop) \%>\%
-  add_lines() \%>\%
-  mutate(rate = unemploy / pop) \%>\% 
-  filter(rate == max(rate))
-plotly_data(p)
-add_markers(p)
-layout(p, annotations = list(x = ~date, y = ~rate, text = "peak"))
-
-# use group_by() + do() + subplot() for trellis displays 
-d <- group_by(mpg, drv)
-plots <- do(d, p = plot_ly(., x = ~cty, name = ~drv))
-subplot(plots[["p"]], nrows = 3, shareX = TRUE)
-
-# arrange displays by their mean
-means <- summarise(d, mn = mean(cty, na.rm = TRUE))
-means \%>\%
-  left_join(plots) \%>\%
-  arrange(mn) \%>\%
-  .[["p"]] \%>\%
-  subplot(nrows = NROW(.), shareX = TRUE)
-  
-# more dplyr verbs applied to plotly objects
-p <- mtcars \%>\%
-  plot_ly(x = ~wt, y = ~mpg, name = "scatter trace") \%>\%
-  add_markers()
-p \%>\% slice(1) \%>\% plotly_data()
-p \%>\% slice(1) \%>\% add_markers(name = "first observation")
-p \%>\% filter(cyl == 4) \%>\% plotly_data()
-p \%>\% filter(cyl == 4) \%>\% add_markers(name = "four cylinders")
-
-
-}