Merge pull request #1434 from plotly/geom_hex

added geom_hex

Author: kojisposts

.gitignore

@@ -22,3 +22,5 @@ vendor/bundle
 _posts/python/fundamentals/static-image/images
 _config_personal.yml
 _posts/python/html
+.Rproj.user
+documentation.Rproj

_posts/ggplot2/2019-07-12-geom_bin2d.Rmd

@@ -39,6 +39,9 @@ packageVersion('plotly')
 ```
 
 ### Basic 2d Heatmap
+See also geom\_hex for a similar geom with hexagonal bins. Note: facetting is supported in geom\_bin2d but not geom\_hex.
+
+Source: [Department of Canadian Heritage](https://open.canada.ca/data/en/dataset/a0bff264-1c80-41ee-aef9-e7da347c5158)
 
 ```{r, results='hide'}
 library(plotly)
@@ -100,7 +103,7 @@ p <- ggplot(english_french, aes(x=engperc, y=frenperc, weight=total)) +
   labs(title = "Distribution of the Canadian population by English and French fluency",
        x = "% fluent in English",
        y = "% fluent in French",
-       fill = "# of people")
+       fill = "population")
 p <- ggplotly(p)
 
 
@@ -127,7 +130,7 @@ 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 people")
+       fill = "population")
 p <- ggplotly(p)
 
 
@@ -154,7 +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 people") +
+       fill = "population") +
   theme_bw() +
   theme(text = element_text(family = 'Fira Sans'))
 p <- ggplotly(p)

_posts/ggplot2/2019-07-12-geom_bin2d.md

@@ -36,11 +36,13 @@ packageVersion('plotly')
 ```
 
 ```
-## [1] '4.9.0'
+## [1] '4.9.0.9000'
 ```
 
 ### Basic 2d Heatmap
+See also [geom_hex](https://plot.ly/ggplot2/geom_hex/) for a similar geom with hexagonal bins. Note: facetting is supported in geom\_bin2d but not geom\_hex.
 
+Source: [Department of Canadian Heritage](https://open.canada.ca/data/en/dataset/a0bff264-1c80-41ee-aef9-e7da347c5158)
 
 ```r
 library(plotly)
@@ -100,7 +102,7 @@ p <- ggplot(english_french, aes(x=engperc, y=frenperc, weight=total)) +
   labs(title = "Distribution of the Canadian population by English and French fluency",
        x = "% fluent in English",
        y = "% fluent in French",
-       fill = "# of people")
+       fill = "population")
 p <- ggplotly(p)
 
 
@@ -113,7 +115,7 @@ 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, and set "bins" to 20, so that the graph is 20 x 20 sides.
+We can facet the graphic with the "region" column, and set "bins" to 20, so that the graph is 20 x 20 sides. 
 
 
 ```r
@@ -126,7 +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 people")
+       fill = "population")
 p <- ggplotly(p)
 
 
@@ -152,7 +154,7 @@ 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 people") +
+       fill = "population") +
   theme_bw() +
   theme(text = element_text(family = 'Fira Sans'))
 p <- ggplotly(p)

_posts/ggplot2/2019-07-30-geom_hex.Rmd

@@ -0,0 +1,153 @@
+---
+title: geom_hex | Examples | Plotly
+name: geom_hex
+permalink: ggplot2/geom_hex/
+description: How to make a hexagonal two-dimensional heatmap in ggplot2 using geom_hex. Examples of coloured and facetted graphs.
+layout: base
+thumbnail: thumbnail/geom_hex.jpg
+language: ggplot2
+page_type: example_index
+has_thumbnail: true
+display_as: statistical
+order: 3
+output:
+  html_document:
+    keep_md: true
+---
+
+```{r, echo = FALSE, message=FALSE}
+knitr::opts_chunk$set(message = FALSE, warning=FALSE)
+Sys.setenv("plotly_username"="RPlotBot")
+Sys.setenv("plotly_api_key"="q0lz6r5efr")
+```
+
+### 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!
+
+### Version Check
+
+Version 4 of Plotly's R package is now [available](https://plot.ly/r/getting-started/#installation)!<br>
+Check out [this post](http://moderndata.plot.ly/upgrading-to-plotly-4-0-and-above/) for more information on breaking changes and new features available in this version.
+
+```{r}
+library(plotly)
+packageVersion('plotly')
+```
+
+### Basic 2d Heatmap
+See also [geom_bin2d](https://plot.ly/ggplot2/geom_bin2d/) for a similar geom with rectangular bins. Note: facetting is supported in geom\_bin2d but not geom\_hex.
+
+Source: [Department of Canadian Heritage](https://open.canada.ca/data/en/dataset/a0bff264-1c80-41ee-aef9-e7da347c5158)
+
+```{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() +
+  labs(title = "Distribution of Canadian areas by English and French fluency",
+       x = "% fluent in English",
+       y = "% fluent in French",
+       fill = "# of census \nsubdivisions")
+p <- 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_hex/2d-chart")
+chart_link
+```
+
+```{r echo=FALSE}
+chart_link
+```
+
+### Customized Colours
+Let's flip the colour scheme so that lighter colours denote larger numbers than darker colours. 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)
+
+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") +
+  labs(title = "Distribution of Canadian towns by English and French fluency",
+       x = "% fluent in English",
+       y = "% fluent in French",
+       fill = "# of census \nsubdivisions")
+p <- 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_hex/log-chart")
+chart_link
+```
+
+```{r echo=FALSE}
+chart_link
+```
+
+### 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.
+
+```{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") +
+  labs(title = "Distribution of the Canadian population by English and French fluency",
+       x = "% fluent in English",
+       y = "% fluent in French",
+       fill = "population")
+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_hex/weighted-data")
+chart_link
+```
+
+```{r echo=FALSE}
+chart_link
+```
+
+### Customized Appearance
+We can modify the graph's appearance - for example, if the grey background makes it difficult to make out the paler shades of blue, we can change the theme to one with a white background. Included also is a way to change the font. You can find a list [here](http://ggplot2.tidyverse.org/reference/theme.html) of all the theme elements that you can modify.
+
+```{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") +
+  labs(title = "Distribution of Canadian towns by English and French fluency",
+       x = "% fluent in English",
+       y = "% fluent in French",
+       fill = "population") +
+  theme_bw() +
+  theme(text = element_text(family = 'Fira Sans'))
+p <- 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_hex/customize-theme")
+chart_link
+```
+
+```{r echo=FALSE}
+chart_link
+```
+

_posts/ggplot2/2019-07-30-geom_hex.md

@@ -0,0 +1,148 @@
+---
+title: geom_hex | Examples | Plotly
+name: geom_hex
+permalink: ggplot2/geom_hex/
+description: How to make a hexagonal two-dimensional heatmap in ggplot2 using geom_hex. Examples of coloured and facetted graphs.
+layout: base
+thumbnail: thumbnail/geom_hex.jpg
+language: ggplot2
+page_type: example_index
+has_thumbnail: true
+display_as: statistical
+order: 3
+output:
+  html_document:
+    keep_md: true
+---
+
+
+
+### 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!
+
+### Version Check
+
+Version 4 of Plotly's R package is now [available](https://plot.ly/r/getting-started/#installation)!<br>
+Check out [this post](http://moderndata.plot.ly/upgrading-to-plotly-4-0-and-above/) for more information on breaking changes and new features available in this version.
+
+
+```r
+library(plotly)
+packageVersion('plotly')
+```
+
+```
+## [1] '4.9.0.9000'
+```
+
+### Basic 2d Heatmap
+See also [geom_bin2d](https://plot.ly/ggplot2/geom_bin2d/) for a similar geom with rectangular bins. Note: facetting is supported in geom\_bin2d but not geom\_hex.
+
+Source: [Department of Canadian Heritage](https://open.canada.ca/data/en/dataset/a0bff264-1c80-41ee-aef9-e7da347c5158)
+
+```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() +
+  labs(title = "Distribution of Canadian areas by English and French fluency",
+       x = "% fluent in English",
+       y = "% fluent in French",
+       fill = "# of census \nsubdivisions")
+p <- 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_hex/2d-chart")
+chart_link
+```
+
+<iframe src="https://plot.ly/~RPlotBot/5729.embed" width="800" height="600" id="igraph" scrolling="no" seamless="seamless" frameBorder="0"> </iframe>
+
+### Customized Colours
+Let's flip the colour scheme so that lighter colours denote larger numbers than darker colours. 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
+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") +
+  labs(title = "Distribution of Canadian towns by English and French fluency",
+       x = "% fluent in English",
+       y = "% fluent in French",
+       fill = "# of census \nsubdivisions")
+p <- 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_hex/log-chart")
+chart_link
+```
+
+<iframe src="https://plot.ly/~RPlotBot/5731.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.
+
+
+```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") +
+  labs(title = "Distribution of the Canadian population by English and French fluency",
+       x = "% fluent in English",
+       y = "% fluent in French",
+       fill = "population")
+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_hex/weighted-data")
+chart_link
+```
+
+<iframe src="https://plot.ly/~RPlotBot/5733.embed" width="800" height="600" id="igraph" scrolling="no" seamless="seamless" frameBorder="0"> </iframe>
+
+### Customized Appearance
+We can modify the graph's appearance - for example, if the grey background makes it difficult to make out the paler shades of blue, we can change the theme to one with a white background. Included also is a way to change the font. You can find a list [here](http://ggplot2.tidyverse.org/reference/theme.html) of all the theme elements that you can modify.
+
+
+```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") +
+  labs(title = "Distribution of Canadian towns by English and French fluency",
+       x = "% fluent in English",
+       y = "% fluent in French",
+       fill = "population") +
+  theme_bw() +
+  theme(text = element_text(family = 'Fira Sans'))
+p <- 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_hex/customize-theme")
+chart_link
+```
+
+<iframe src="https://plot.ly/~RPlotBot/5739.embed" width="800" height="600" id="igraph" scrolling="no" seamless="seamless" frameBorder="0"> </iframe>
+