Pie Charts in R

How to make pie charts in R using plotly.

New to Plotly?

Plotly is a free and open-source graphing library for R. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.

Basic Pie Chart

library(plotly)

USPersonalExpenditure <- data.frame("Categorie"=rownames(USPersonalExpenditure), USPersonalExpenditure)
data <- USPersonalExpenditure[,c('Categorie', 'X1960')]

fig <- plot_ly(data, labels = ~Categorie, values = ~X1960, type = 'pie')
fig <- fig %>% layout(title = 'United States Personal Expenditures by Categories in 1960',
         xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
         yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))

fig

Styled Pie Chart

library(plotly)

USPersonalExpenditure <- data.frame("Categorie" = rownames(USPersonalExpenditure), USPersonalExpenditure)
data <- USPersonalExpenditure[, c('Categorie', 'X1960')]

colors <- c('rgb(211,94,96)', 'rgb(128,133,133)', 'rgb(144,103,167)', 'rgb(171,104,87)', 'rgb(114,147,203)')

fig <- plot_ly(data, labels = ~Categorie, values = ~X1960, type = 'pie',
        textposition = 'inside',
        textinfo = 'label+percent',
        insidetextfont = list(color = '#FFFFFF'),
        hoverinfo = 'text',
        text = ~paste('$', X1960, ' billions'),
        marker = list(colors = colors,
                      line = list(color = '#FFFFFF', width = 1)),
                      #The 'pull' attribute can also be used to create space between the sectors
        showlegend = FALSE)
fig <- fig %>% layout(title = 'United States Personal Expenditures by Categories in 1960',
         xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
         yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))

fig

Subplots

In order to create pie chart subplots, you need to use the domain attribute. It is important to note that the X array set the horizontal position whilst the Y array sets the vertical. For example, x=[0,0.5], y=[0, 0.5] would mean the bottom left position of the plot.

library(plotly)
library(dplyr)

fig <- plot_ly()
fig <- fig %>% add_pie(data = count(diamonds, cut), labels = ~cut, values = ~n,
          name = "Cut", domain = list(x = c(0, 0.4), y = c(0.4, 1)))
fig <- fig %>% add_pie(data = count(diamonds, color), labels = ~color, values = ~n,
          name = "Color", domain = list(x = c(0.6, 1), y = c(0.4, 1)))
fig <- fig %>% add_pie(data = count(diamonds, clarity), labels = ~clarity, values = ~n,
          name = "Clarity", domain = list(x = c(0.25, 0.75), y = c(0, 0.6)))
fig <- fig %>% layout(title = "Pie Charts with Subplots", showlegend = F,
         xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
         yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))

fig

Subplots Using Grid

This example uses a plotly grid attribute for the suplots. Reference the row and column destination using the domain attribute.

library(plotly)
library(dplyr)

fig <- plot_ly()
fig <- fig %>% add_pie(data = count(diamonds, cut), labels = ~cut, values = ~n,
                         name = "Cut", domain = list(row = 0, column = 0))
fig <- fig %>% add_pie(data = count(diamonds, color), labels = ~color, values = ~n,
                       name = "Color", domain = list(row = 0, column = 1))
fig <- fig %>% add_pie(data = count(diamonds, clarity), labels = ~clarity, values = ~n,
                       name = "Clarity", domain = list(row = 1, column = 0))
fig <- fig %>% add_pie(data = count(diamonds, cut), labels = ~cut, values = ~n,
                       name = "Clarity", domain = list(row = 1, column = 1))
fig <- fig %>% layout(title = "Pie Charts with Subplots", showlegend = F,
                      grid=list(rows=2, columns=2),
                      xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
                      yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))

fig

See more examples of subplots here.

Controlling text orientation inside sunburst sectors

The insidetextorientation attribute controls the orientation of text inside sectors. With "auto" the texts may automatically be rotated to fit with the maximum size inside the slice. Using "horizontal" (resp. "radial", "tangential") forces text to be horizontal (resp. radial or tangential). Note that plotly may reduce the font size in order to fit the text with the requested orientation.

library(plotly)

labels = c('Oxygen','Hydrogen','Carbon_Dioxide','Nitrogen')
values = c(4500, 2500, 1053, 500)

fig <- plot_ly(type='pie', labels=labels, values=values, 
               textinfo='label+percent',
               insidetextorientation='radial')
fig

Donut Chart

library(plotly)
library(dplyr)

# Get Manufacturer
mtcars$manuf <- sapply(strsplit(rownames(mtcars), " "), "[[", 1)

df <- mtcars
df <- df %>% group_by(manuf)
df <- df %>% summarize(count = n())
fig <- df %>% plot_ly(labels = ~manuf, values = ~count)
fig <- fig %>% add_pie(hole = 0.6)
fig <- fig %>% layout(title = "Donut charts using Plotly",  showlegend = F,
                      xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
                      yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))

fig

Reference

See https://plotly.com/r/reference/#pie for more information and chart attribute options!

What About Dash?

Dash for R is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Learn about how to install Dash for R at https://dashr.plot.ly/installation.

Everywhere in this page that you see fig, you can display the same figure in a Dash for R application by passing it to the figure argument of the Graph component from the built-in dashCoreComponents package like this:

library(plotly)

fig <- plot_ly() 
# fig <- fig %>% add_trace( ... )
# fig <- fig %>% layout( ... ) 

library(dash)
library(dashCoreComponents)
library(dashHtmlComponents)

app <- Dash$new()
app$layout(
    htmlDiv(
        list(
            dccGraph(figure=fig) 
        )
     )
)

app$run_server(debug=TRUE, dev_tools_hot_reload=FALSE)