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added geom_hex, fixed problems with geom_bin2d
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‎_posts/ggplot2/2019-07-12-geom_bin2d.Rmd

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@@ -39,6 +39,7 @@ packageVersion('plotly')
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```
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### Basic 2d Heatmap
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See also geom\_hex for a similar geom with hexagonal bins. Note: facetting is supported in geom\_bin2d but not geom\_hex.
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```{r, results='hide'}
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library(plotly)
@@ -100,7 +101,7 @@ p <- ggplot(english_french, aes(x=engperc, y=frenperc, weight=total)) +
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labs(title = "Distribution of the Canadian population by English and French fluency",
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x = "% fluent in English",
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y = "% fluent in French",
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fill = "# of people")
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fill = "population")
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p <- ggplotly(p)
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@@ -127,7 +128,7 @@ p <- ggplot(english_french, aes(x=engperc,y=frenperc, weight=total)) +
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labs(title = "Distribution of Canadian towns by English and French fluency",
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x = "% fluent in English",
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y = "% fluent in French",
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fill = "# of people")
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fill = "population")
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p <- ggplotly(p)
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@@ -154,7 +155,7 @@ p <- ggplot(english_french, aes(x=engperc,y=frenperc, weight=total)) +
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labs(title = "Distribution of Canadian towns by English and French fluency",
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x = "% fluent in English",
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y = "% fluent in French",
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fill = "# of people") +
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fill = "population") +
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theme_bw() +
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theme(text = element_text(family = 'Fira Sans'))
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p <- ggplotly(p)

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

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@@ -36,10 +36,11 @@ packageVersion('plotly')
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```
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```
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## [1] '4.9.0'
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## [1] '4.9.0.9000'
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```
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### Basic 2d Heatmap
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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.
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```r
@@ -100,7 +101,7 @@ p <- ggplot(english_french, aes(x=engperc, y=frenperc, weight=total)) +
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labs(title = "Distribution of the Canadian population by English and French fluency",
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x = "% fluent in English",
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y = "% fluent in French",
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fill = "# of people")
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fill = "population")
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p <- ggplotly(p)
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@@ -113,7 +114,7 @@ chart_link
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<iframe src="https://plot.ly/~RPlotBot/5680.embed" width="800" height="600" id="igraph" scrolling="no" seamless="seamless" frameBorder="0"> </iframe>
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### With Facets
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We can facet the graphic with the "region" column, and set "bins" to 20, so that the graph is 20 x 20 sides.
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We can facet the graphic with the "region" column, and set "bins" to 20, so that the graph is 20 x 20 sides.
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```r
@@ -126,7 +127,7 @@ p <- ggplot(english_french, aes(x=engperc,y=frenperc, weight=total)) +
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labs(title = "Distribution of Canadian towns by English and French fluency",
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x = "% fluent in English",
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y = "% fluent in French",
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fill = "# of people")
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fill = "population")
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p <- ggplotly(p)
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@@ -152,7 +153,7 @@ p <- ggplot(english_french, aes(x=engperc,y=frenperc, weight=total)) +
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labs(title = "Distribution of Canadian towns by English and French fluency",
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x = "% fluent in English",
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y = "% fluent in French",
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fill = "# of people") +
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fill = "population") +
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theme_bw() +
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theme(text = element_text(family = 'Fira Sans'))
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p <- ggplotly(p)

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

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---
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title: geom_hex | Examples | Plotly
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name: geom_hex
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permalink: ggplot2/geom_hex/
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description: How to make a hexagonal two-dimensional heatmap in ggplot2 using geom_hex. Examples of coloured and facetted graphs.
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layout: base
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thumbnail: thumbnail/geom_hex.jpg
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language: ggplot2
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page_type: example_index
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has_thumbnail: true
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display_as: statistical
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order: 3
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output:
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html_document:
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keep_md: true
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---
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```{r, echo = FALSE, message=FALSE}
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knitr::opts_chunk$set(message = FALSE, warning=FALSE)
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Sys.setenv("plotly_username"="RPlotBot")
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Sys.setenv("plotly_api_key"="q0lz6r5efr")
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```
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### New to Plotly?
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Plotly's R library is free and open source!<br>
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[Get started](https://plot.ly/r/getting-started/) by downloading the client and [reading the primer](https://plot.ly/r/getting-started/).<br>
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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>
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We also have a quick-reference [cheatsheet](https://images.plot.ly/plotly-documentation/images/r_cheat_sheet.pdf) (new!) to help you get started!
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### Version Check
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Version 4 of Plotly's R package is now [available](https://plot.ly/r/getting-started/#installation)!<br>
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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.
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```{r}
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library(plotly)
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packageVersion('plotly')
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```
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### Basic 2d Heatmap
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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.
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```{r, results='hide'}
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library(plotly)
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english_french <- read.csv("https://raw.githubusercontent.com/plotly/datasets/master/english_french.csv",stringsAsFactors = FALSE)
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p <- ggplot(english_french, aes(x=engperc,y=frenperc)) +
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geom_hex() +
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labs(title = "Distribution of Canadian areas by English and French fluency",
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x = "% fluent in English",
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y = "% fluent in French",
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fill = "# of census \nsubdivisions")
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p <- ggplotly(p)
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# Create a shareable link to your chart
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# Set up API credentials: https://plot.ly/r/getting-started
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chart_link = api_create(p, filename="geom_hex/2d-chart")
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chart_link
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```
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```{r echo=FALSE}
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chart_link
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```
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### Customized Colours
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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.
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```{r, results='hide'}
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library(plotly)
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p <- ggplot(english_french, aes(x=engperc,y=frenperc)) +
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geom_hex() +
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scale_fill_gradient(low="lightblue1",high="darkblue",trans="log10") +
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labs(title = "Distribution of Canadian towns by English and French fluency",
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x = "% fluent in English",
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y = "% fluent in French",
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fill = "# of census \nsubdivisions")
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p <- ggplotly(p)
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# Create a shareable link to your chart
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# Set up API credentials: https://plot.ly/r/getting-started
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chart_link = api_create(p, filename="geom_hex/log-chart")
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chart_link
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```
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```{r echo=FALSE}
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chart_link
90+
```
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### Weighted Data
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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.
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```{r, results='hide'}
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library(plotly)
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p <- ggplot(english_french, aes(x=engperc, y=frenperc, weight=total)) +
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geom_hex() +
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scale_fill_gradient(low="lightblue1",high="darkblue",trans="log10") +
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labs(title = "Distribution of the Canadian population by English and French fluency",
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x = "% fluent in English",
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y = "% fluent in French",
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fill = "population")
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ggplotly(p)
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# Create a shareable link to your chart
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# Set up API credentials: https://plot.ly/r/getting-started
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chart_link = api_create(p, filename="geom_hex/weighted-data")
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chart_link
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```
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```{r echo=FALSE}
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chart_link
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```
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### Customized Appearance
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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.
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```{r, results='hide'}
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library(plotly)
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p <- ggplot(english_french, aes(x=engperc,y=frenperc, weight=total)) +
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geom_hex(bins = 20) +
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scale_fill_gradient(low="lightblue1",high="darkblue",trans="log10") +
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labs(title = "Distribution of Canadian towns by English and French fluency",
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x = "% fluent in English",
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y = "% fluent in French",
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fill = "population") +
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theme_bw() +
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theme(text = element_text(family = 'Fira Sans'))
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p <- ggplotly(p)
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# Create a shareable link to your chart
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# Set up API credentials: https://plot.ly/r/getting-started
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chart_link = api_create(p, filename="geom_hex/customize-theme")
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chart_link
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```
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```{r echo=FALSE}
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chart_link
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```
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‎_posts/ggplot2/2019-07-30-geom_hex.md

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---
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title: geom_hex | Examples | Plotly
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name: geom_hex
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permalink: ggplot2/geom_hex/
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description: How to make a hexagonal two-dimensional heatmap in ggplot2 using geom_hex. Examples of coloured and facetted graphs.
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layout: base
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thumbnail: thumbnail/geom_hex.jpg
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language: ggplot2
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page_type: example_index
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has_thumbnail: true
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display_as: statistical
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order: 3
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output:
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html_document:
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keep_md: true
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---
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18+
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### New to Plotly?
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22+
Plotly's R library is free and open source!<br>
23+
[Get started](https://plot.ly/r/getting-started/) by downloading the client and [reading the primer](https://plot.ly/r/getting-started/).<br>
24+
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>
25+
We also have a quick-reference [cheatsheet](https://images.plot.ly/plotly-documentation/images/r_cheat_sheet.pdf) (new!) to help you get started!
26+
27+
### Version Check
28+
29+
Version 4 of Plotly's R package is now [available](https://plot.ly/r/getting-started/#installation)!<br>
30+
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.
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32+
33+
```r
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library(plotly)
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packageVersion('plotly')
36+
```
37+
38+
```
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## [1] '4.9.0.9000'
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```
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### Basic 2d Heatmap
43+
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.
44+
45+
46+
```r
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library(plotly)
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english_french <- read.csv("https://raw.githubusercontent.com/plotly/datasets/master/english_french.csv",stringsAsFactors = FALSE)
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p <- ggplot(english_french, aes(x=engperc,y=frenperc)) +
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geom_hex() +
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labs(title = "Distribution of Canadian areas by English and French fluency",
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x = "% fluent in English",
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y = "% fluent in French",
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fill = "# of census \nsubdivisions")
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p <- ggplotly(p)
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# Create a shareable link to your chart
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# Set up API credentials: https://plot.ly/r/getting-started
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chart_link = api_create(p, filename="geom_hex/2d-chart")
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chart_link
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```
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<iframe src="https://plot.ly/~RPlotBot/5729.embed" width="800" height="600" id="igraph" scrolling="no" seamless="seamless" frameBorder="0"> </iframe>
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### Customized Colours
68+
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.
69+
70+
71+
```r
72+
library(plotly)
73+
74+
p <- ggplot(english_french, aes(x=engperc,y=frenperc)) +
75+
geom_hex() +
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scale_fill_gradient(low="lightblue1",high="darkblue",trans="log10") +
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labs(title = "Distribution of Canadian towns by English and French fluency",
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x = "% fluent in English",
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y = "% fluent in French",
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fill = "# of census \nsubdivisions")
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p <- ggplotly(p)
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# Create a shareable link to your chart
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# Set up API credentials: https://plot.ly/r/getting-started
85+
chart_link = api_create(p, filename="geom_hex/log-chart")
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chart_link
87+
```
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<iframe src="https://plot.ly/~RPlotBot/5731.embed" width="800" height="600" id="igraph" scrolling="no" seamless="seamless" frameBorder="0"> </iframe>
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### Weighted Data
92+
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.
93+
94+
95+
```r
96+
library(plotly)
97+
98+
p <- ggplot(english_french, aes(x=engperc, y=frenperc, weight=total)) +
99+
geom_hex() +
100+
scale_fill_gradient(low="lightblue1",high="darkblue",trans="log10") +
101+
labs(title = "Distribution of the Canadian population by English and French fluency",
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x = "% fluent in English",
103+
y = "% fluent in French",
104+
fill = "population")
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ggplotly(p)
106+
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# Create a shareable link to your chart
108+
# Set up API credentials: https://plot.ly/r/getting-started
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chart_link = api_create(p, filename="geom_hex/weighted-data")
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chart_link
111+
```
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<iframe src="https://plot.ly/~RPlotBot/5733.embed" width="800" height="600" id="igraph" scrolling="no" seamless="seamless" frameBorder="0"> </iframe>
114+
115+
### Customized Appearance
116+
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.
117+
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```r
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library(plotly)
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p <- ggplot(english_french, aes(x=engperc,y=frenperc, weight=total)) +
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geom_hex(bins = 20) +
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scale_fill_gradient(low="lightblue1",high="darkblue",trans="log10") +
125+
labs(title = "Distribution of Canadian towns by English and French fluency",
126+
x = "% fluent in English",
127+
y = "% fluent in French",
128+
fill = "population") +
129+
theme_bw() +
130+
theme(text = element_text(family = 'Fira Sans'))
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p <- ggplotly(p)
132+
133+
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# Create a shareable link to your chart
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# Set up API credentials: https://plot.ly/r/getting-started
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chart_link = api_create(p, filename="geom_hex/customize-theme")
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chart_link
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```
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<iframe src="https://plot.ly/~RPlotBot/5739.embed" width="800" height="600" id="igraph" scrolling="no" seamless="seamless" frameBorder="0"> </iframe>
141+

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