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Merge pull request plotly#1453 from plotly/geom_tile
new version of geom_tile
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_posts/ggplot2/2016-11-29-geom_tile.Rmd

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_posts/ggplot2/2016-11-29-geom_tile.md

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---
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title: geom_tile | Examples | Plotly
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name: geom_tile
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permalink: ggplot2/geom_tile/
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description: How to make a 2-dimensional heatmap in ggplot2 using geom_tile.
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layout: base
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thumbnail: thumbnail/geom_tile.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: basic
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order: 8
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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 geom\_tile graph
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This graph, compiled by [Jeff Zimmerman](https://docs.google.com/spreadsheets/d/1HI-dikWN64clxSGJu2QV8C64R9Bkzt8K-jFaeHj4X7k/edit#gid=0), shows how often hitters swing and miss at fastballs, based on their velocity and spin rate. Colour schemes are from ColorBrewer; a complete list of palettes is available [here](https://ggplot2.tidyverse.org/reference/scale_brewer.html).
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```{r, results='hide'}
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library(plotly)
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spinrates <- read.csv("https://raw.githubusercontent.com/plotly/datasets/master/spinrates.csv",
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stringsAsFactors = FALSE)
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p <- ggplot(spinrates, aes(x=velocity, y=spinrate)) +
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geom_tile(aes(fill = swing_miss)) +
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scale_fill_distiller(palette = "YlGnBu") +
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labs(title = "Likelihood of swinging and missing on a fastball",
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y = "spin rate (rpm)")
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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_tile/distilled-colour")
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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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### Adjusting appearance
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The *direction* option sets which side of the colour scheme maps onto the low values and which side maps onto the high; it defaults to -1 but could be adjusted to 1.
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Also [adjusted the theme](https://ggplot2.tidyverse.org/reference/ggtheme.html).
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```{r, results='hide'}
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library(plotly)
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spinrates <- read.csv("https://raw.githubusercontent.com/plotly/datasets/master/spinrates.csv",
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stringsAsFactors = FALSE)
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p <- ggplot(spinrates, aes(x=velocity, y=spinrate)) +
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geom_tile(aes(fill = swing_miss)) +
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scale_fill_distiller(palette = "YlGnBu", direction = 1) +
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theme_light() +
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labs(title = "Likelihood of swinging and missing on a fastball",
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y = "spin rate (rpm)")
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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_tile/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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### geom\_tile with viridis colour scheme
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[Viridis colour schemes](https://ggplot2.tidyverse.org/reference/scale_brewer.html) are uniform in both colour and black-and-white, as well as for those with colour-blindness. There are five colour schemes: "magma" (or "A"), "inferno" (or "B"), "plasma" (or "C"), "viridis" (or "D", the default option) and "cividis" (or "E").
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```{r, results='hide'}
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library(plotly)
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spinrates <- read.csv("https://raw.githubusercontent.com/plotly/datasets/master/spinrates.csv",
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stringsAsFactors = FALSE)
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p <- ggplot(spinrates, aes(x=velocity, y=spinrate)) +
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geom_tile(aes(fill = swing_miss)) +
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scale_fill_viridis_c(option = "B", direction = -1) +
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labs(title = "Likelihood of swinging and missing on a fastball",
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y = "spin rate (rpm)") +
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theme_light()
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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_tile/viridis")
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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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