edited

kojisposts · kojisposts · commit 784241bad35d · 2019-08-12T17:40:04.000-04:00
diff --git a/_posts/ggplot2/2019-07-30-geom_hex.Rmd b/_posts/ggplot2/2019-07-30-geom_hex.Rmd
@@ -72,6 +72,8 @@ Let's flip the colour scheme so that lighter colours denote larger numbers than
 ```{r, results='hide'}
 library(plotly)
 
+english_french <- read.csv("https://raw.githubusercontent.com/plotly/datasets/master/english_french.csv",stringsAsFactors = FALSE)
+
 p <- ggplot(english_french, aes(x=engperc,y=frenperc)) + 
   geom_hex() +
   scale_fill_gradient(low="lightblue1",high="darkblue",trans="log10") +
@@ -97,6 +99,8 @@ In the previous graphs, each observation represented a single census subdivision
 ```{r, results='hide'}
 library(plotly)
 
+english_french <- read.csv("https://raw.githubusercontent.com/plotly/datasets/master/english_french.csv",stringsAsFactors = FALSE)
+
 p <- ggplot(english_french, aes(x=engperc, y=frenperc, weight=total)) + 
   geom_hex() +
   scale_fill_gradient(low="lightblue1",high="darkblue",trans="log10") +
@@ -123,6 +127,8 @@ We can modify the graph's appearance - for example, if the grey background makes
 ```{r, results='hide'}
 library(plotly)
 
+english_french <- read.csv("https://raw.githubusercontent.com/plotly/datasets/master/english_french.csv",stringsAsFactors = FALSE)
+
 p <- ggplot(english_french, aes(x=engperc,y=frenperc, weight=total)) + 
   geom_hex(bins = 20) +
   scale_fill_gradient(low="lightblue1",high="darkblue",trans="log10") +
diff --git a/_posts/ggplot2/2019-07-30-geom_hex.md b/_posts/ggplot2/2019-07-30-geom_hex.md
@@ -72,6 +72,8 @@ Let's flip the colour scheme so that lighter colours denote larger numbers than
 ```r
 library(plotly)
 
+english_french <- read.csv("https://raw.githubusercontent.com/plotly/datasets/master/english_french.csv",stringsAsFactors = FALSE)
+
 p <- ggplot(english_french, aes(x=engperc,y=frenperc)) + 
   geom_hex() +
   scale_fill_gradient(low="lightblue1",high="darkblue",trans="log10") +
@@ -96,6 +98,8 @@ In the previous graphs, each observation represented a single census subdivision
 ```r
 library(plotly)
 
+english_french <- read.csv("https://raw.githubusercontent.com/plotly/datasets/master/english_french.csv",stringsAsFactors = FALSE)
+
 p <- ggplot(english_french, aes(x=engperc, y=frenperc, weight=total)) + 
   geom_hex() +
   scale_fill_gradient(low="lightblue1",high="darkblue",trans="log10") +
@@ -120,6 +124,8 @@ We can modify the graph's appearance - for example, if the grey background makes
 ```r
 library(plotly)
 
+english_french <- read.csv("https://raw.githubusercontent.com/plotly/datasets/master/english_french.csv",stringsAsFactors = FALSE)
+
 p <- ggplot(english_french, aes(x=engperc,y=frenperc, weight=total)) + 
   geom_hex(bins = 20) +
   scale_fill_gradient(low="lightblue1",high="darkblue",trans="log10") +
