Area chart with R and ggplot2



This post is a step by step introduction to area chart with R and ggplot2. It provides several reproducible examples with explanation and R code.

Area chart Section About area chart

Basic line chart with ggplot2 and geom_line()


An area chart displays the evolution of one or several numeric variables. Data points are usually connected by straight line segments, and the area between the X axis and the line is filled. See data-to-viz for a more in-depth definition.

As for a line chart, the input data frame requires at least 2 columns:

  • An ordered numeric variable for the X axis
  • Another numeric variable for the Y axis

Once the data is read by ggplot2 and those 2 variables are specified in the x and y arguments of the aes(), just call the geom_area() function.

# Libraries
library(ggplot2)

# create data
xValue <- 1:50
yValue <- cumsum(rnorm(50))
data <- data.frame(xValue,yValue)

# Plot
ggplot(data, aes(x=xValue, y=yValue)) +
  geom_area()

Customize the line chart


Several options are available to customize the area chart appearance:

  • Add a title with ggtitle().
  • Change line style with arguments like shape, size, color and more.
  • Add transparency to the filled region with opacity
  • Custom the general theme with the theme_ipsum() function of the hrbrthemes package.
  • Highlight the top line with geom_line()
  • If not too many observation, show individual data points with geom_point()

More generally, visit the [ggplot2 section] for more ggplot2 related stuff.

# Libraries
library(ggplot2)
library(hrbrthemes)

# create data
xValue <- 1:10
yValue <- abs(cumsum(rnorm(10)))
data <- data.frame(xValue,yValue)

# Plot
ggplot(data, aes(x=xValue, y=yValue)) +
  geom_area( fill="#69b3a2", alpha=0.4) +
  geom_line(color="#69b3a2", size=2) +
  geom_point(size=3, color="#69b3a2") +
  theme_ipsum() +
  ggtitle("Evolution of something")

Related chart types


Line plot
Area
Stacked area
Streamchart
Time Series



Contact

This document is a work by Yan Holtz. Any feedback is highly encouraged. You can fill an issue on Github, drop me a message on Twitter, or send an email pasting yan.holtz.data with gmail.com.

Github Twitter