final version of geom_bin2d, and also finally fixed the initial test edits

kojisposts · kojisposts · commit 06691ab8fdb2 · 2019-07-17T11:45:52.000-04:00
diff --git a/2017-04-21-geom_quantile.md b/2017-04-21-geom_quantile.md
diff --git a/_posts/ggplot2/2017-04-21-geom_quantile.md b/_posts/ggplot2/2017-04-21-geom_quantile.md
@@ -17,13 +17,13 @@ output:
 
 
 
-### New to Plotly??!!?
+### New to Plotly?
 
 Plotly's R library is free and open source!<br>
 [Get started](https://plot.ly/r/getting-started/) by downloading the client and [reading the primer](https://plot.ly/r/getting-started/).<br>
 You can set up Plotly to work in [online](https://plot.ly/r/getting-started/#hosting-graphs-in-your-online-plotly-account) or [offline](https://plot.ly/r/offline/) mode.<br>
 We also have a quick-reference [cheatsheet](https://images.plot.ly/plotly-documentation/images/r_cheat_sheet.pdf) (new!) to help you get started!
-2017-04-21-geom_quantile.Rmd
+
 ### Version Check
 
 Version 4 of Plotly's R package is now [available](https://plot.ly/r/getting-started/#installation)!<br>
diff --git a/_posts/ggplot2/2019-07-12-geom_bin2d.Rmd b/_posts/ggplot2/2019-07-12-geom_bin2d.Rmd
@@ -2,13 +2,13 @@
 title: geom_bin2d | Examples | Plotly
 name: geom_bin2d
 permalink: ggplot2/geom_bin2d/
-description: How to make a bar chart in ggplot2 using geom_bin2d. Examples of filled and facetted bar charts. [UPDATE]
+description: How to make a 2-dimensional heatmap in ggplot2 using geom_bin2d. Examples of coloured and facetted graphs.
 layout: base
-thumbnail: thumbnail/bar.jpg [ADD]
+thumbnail: thumbnail/geom_bin2d.jpg
 language: ggplot2
 page_type: example_index
 has_thumbnail: true
-display_as: basic
+display_as: statistical
 order: 2
 output:
   html_document:
@@ -47,7 +47,7 @@ english_french <- read.csv("https://raw.githubusercontent.com/plotly/datasets/ma
 
 p <- ggplot(english_french, aes(x=engperc,y=frenperc)) + 
   geom_bin2d() +
-  labs(title = "Distribution of Canadian towns by English and French fluency",
+  labs(title = "Distribution of Canadian areas by English and French fluency",
        x = "% fluent in English",
        y = "% fluent in French",
        fill = "# of census \nsubdivisions")
@@ -65,7 +65,7 @@ chart_link
 
 ### Customized Colours
 The automatic colour scheme is unintuitive: lighter colours denote larger numbers than darker colours.
-We should change that, and while we're at it, make the colour scale logarithmic.
+We should change that by setting our own colour scale. We should also move to a logarithmic scale, since as it is, the very large value in the bottom right overshadows all other values.
 
 ```{r, results='hide'}
 library(plotly)
@@ -81,7 +81,7 @@ ggplotly(p)
 
 # Create a shareable link to your chart
 # Set up API credentials: https://plot.ly/r/getting-started
-chart_link = api_create(p, filename="geom_bin2d/coloured-chart")
+chart_link = api_create(p, filename="geom_bin2d/log-chart")
 chart_link
 ```
 
@@ -97,7 +97,6 @@ library(plotly)
 
 p <- ggplot(english_french, aes(x=engperc, y=frenperc, weight=total)) + 
   geom_bin2d() +
-  geom_bin2d(data = transform(english_french,region = "All"),bins = 20) +
   scale_fill_gradient(low="lightblue1",high="darkblue",trans="log10") +
   labs(title = "Distribution of the Canadian population by English and French fluency",
        x = "% fluent in English",
@@ -117,7 +116,7 @@ chart_link
 ```
 
 ### With Facets
-We can facet the graphic with the "region" column. We can also use a little trick to add an "All" subset containing all the data.
+We can facet the graphic with the "region" column, and set "bins" to 20, so that the graph is 20 x 20 sides. We can also use a little trick to add an "All" subset containing all the data.
 
 ```{r, results='hide'}
 library(plotly)
@@ -130,7 +129,7 @@ p <- ggplot(english_french, aes(x=engperc,y=frenperc, weight=total)) +
   labs(title = "Distribution of Canadian towns by English and French fluency",
        x = "% fluent in English",
        y = "% fluent in French",
-       fill = "# of census \nsubdivisions")
+       fill = "# of people")
 ggplotly(p)
 
 
@@ -158,7 +157,7 @@ p <- ggplot(english_french, aes(x=engperc,y=frenperc, weight=total)) +
   labs(title = "Distribution of Canadian towns by English and French fluency",
        x = "% fluent in English",
        y = "% fluent in French",
-       fill = "# of census \nsubdivisions") +
+       fill = "# of people") +
   theme_bw() +
   theme(text = element_text(family = 'Fira Sans'))
 ggplotly(p)
diff --git a/_posts/ggplot2/2019-07-12-geom_bin2d.md b/_posts/ggplot2/2019-07-12-geom_bin2d.md
@@ -2,13 +2,13 @@
 title: geom_bin2d | Examples | Plotly
 name: geom_bin2d
 permalink: ggplot2/geom_bin2d/
-description: How to make a bar chart in ggplot2 using geom_bin2d. Examples of filled and facetted bar charts. [UPDATE]
+description: How to make a 2-dimensional heatmap in ggplot2 using geom_bin2d. Examples of coloured and facetted graphs.
 layout: base
-thumbnail: thumbnail/bar.jpg [ADD]
+thumbnail: thumbnail/geom_bin2d.jpg
 language: ggplot2
 page_type: example_index
 has_thumbnail: true
-display_as: basic
+display_as: statistical
 order: 2
 output:
   html_document:
@@ -49,7 +49,7 @@ english_french <- read.csv("https://raw.githubusercontent.com/plotly/datasets/ma
 
 p <- ggplot(english_french, aes(x=engperc,y=frenperc)) + 
   geom_bin2d() +
-  labs(title = "Distribution of Canadian towns by English and French fluency",
+  labs(title = "Distribution of Canadian areas by English and French fluency",
        x = "% fluent in English",
        y = "% fluent in French",
        fill = "# of census \nsubdivisions")
@@ -65,7 +65,7 @@ chart_link
 
 ### Customized Colours
 The automatic colour scheme is unintuitive: lighter colours denote larger numbers than darker colours.
-We should change that, and while we're at it, make the colour scale logarithmic.
+We should change that by setting our own colour scale. We should also move to a logarithmic scale, since as it is, the very large value in the bottom right overshadows all other values.
 
 
 ```r
@@ -82,11 +82,11 @@ ggplotly(p)
 
 # Create a shareable link to your chart
 # Set up API credentials: https://plot.ly/r/getting-started
-chart_link = api_create(p, filename="geom_bin2d/coloured-chart")
+chart_link = api_create(p, filename="geom_bin2d/log-chart")
 chart_link
 ```
 
-<iframe src="https://plot.ly/~RPlotBot/5676.embed" width="800" height="600" id="igraph" scrolling="no" seamless="seamless" frameBorder="0"> </iframe>
+<iframe src="https://plot.ly/~RPlotBot/5682.embed" width="800" height="600" id="igraph" scrolling="no" seamless="seamless" frameBorder="0"> </iframe>
 
 ### Weighted Data
 In the previous graphs, each observation represented a single census subdivision - this counted small towns of 500 people equally with cities like Montreal and Toronto. We can weight the data by the "total" column (i.e. total population) to make this a graph of population.
@@ -97,7 +97,6 @@ library(plotly)
 
 p <- ggplot(english_french, aes(x=engperc, y=frenperc, weight=total)) + 
   geom_bin2d() +
-  geom_bin2d(data = transform(english_french,region = "All"),bins = 20) +
   scale_fill_gradient(low="lightblue1",high="darkblue",trans="log10") +
   labs(title = "Distribution of the Canadian population by English and French fluency",
        x = "% fluent in English",
@@ -115,7 +114,7 @@ chart_link
 <iframe src="https://plot.ly/~RPlotBot/5680.embed" width="800" height="600" id="igraph" scrolling="no" seamless="seamless" frameBorder="0"> </iframe>
 
 ### With Facets
-We can facet the graphic with the "region" column. We can also use a little trick to add an "All" subset containing all the data.
+We can facet the graphic with the "region" column, and set "bins" to 20, so that the graph is 20 x 20 sides. We can also use a little trick to add an "All" subset containing all the data.
 
 
 ```r
@@ -129,7 +128,7 @@ p <- ggplot(english_french, aes(x=engperc,y=frenperc, weight=total)) +
   labs(title = "Distribution of Canadian towns by English and French fluency",
        x = "% fluent in English",
        y = "% fluent in French",
-       fill = "# of census \nsubdivisions")
+       fill = "# of people")
 ggplotly(p)
 
 
@@ -156,7 +155,7 @@ p <- ggplot(english_french, aes(x=engperc,y=frenperc, weight=total)) +
   labs(title = "Distribution of Canadian towns by English and French fluency",
        x = "% fluent in English",
        y = "% fluent in French",
-       fill = "# of census \nsubdivisions") +
+       fill = "# of people") +
   theme_bw() +
   theme(text = element_text(family = 'Fira Sans'))
 ggplotly(p)
