Table of Contents
Histograms by group can be created in ggplot2 by using the facet_grid() function. This function allows you to break down a dataset into separate groups and create a histogram for each group. To create a histogram by group, you must first set up your data in a long format, then define the x and y-axis, and then call the facet_grid() function, specifying the column containing the groups. An example of this is the mpg dataset in the ggplot2 library, which contains a column for the number of cylinders in a car. By calling facet_grid(cyl ~ .), a histogram of mpg for each cylinder group is created.
You can use the following basic syntax to create a histogram by group in ggplot2:
ggplot(df, aes(x=values_var, fill=group_var)) + geom_histogram(color='black', alpha=0.4, position='identity') + scale_fill_manual(values=c('red', 'blue', 'purple'))
This particular example creates a plot with three overlaid histograms that are red, blue, and purple.
The following example show how to use this syntax in practice.
Example: Create Histogram by Group in ggplot2
Suppose we have the following data frame in R that contains information about points scored by basketball players on three different teams:
#make this example reproducible
set.seed(1)
#create data frame
df <- data.frame(team=rep(c('A', 'B', 'C'), each=100),
points=c(rnorm(100, mean=10),
rnorm(100, mean=15),
rnorm(100, mean=20)))
#view head of data frame
head(df)
team points
1 A 9.373546
2 A 10.183643
3 A 9.164371
4 A 11.595281
5 A 10.329508
6 A 9.179532
We can use the following code to create histograms that display the distribution of points scored by each of the three teams:
library(ggplot2)
#create histogram by team
ggplot(df, aes(x=points, fill=team)) +
geom_histogram(color='black', alpha=0.4, position='identity') +
scale_fill_manual(values=c('red', 'blue', 'purple'))
The three histograms represent the distribution of points scored by players on each team.
The legend on the right side of the plot shows which color corresponds with each team.
Note that the color argument specifies the outline color for the bars in each histogram and the alpha argument specifies the transparency (between 0 and 1) to use for the bars.
By setting the value for alpha to be less than 1, we’re able to see any overlapping bars between the histograms.
Feel free to use the labs() function to modify the labels in the plot and choose a that fits your style:
library(ggplot2)
#create histogram by team
ggplot(df, aes(x=points, fill=team)) +
geom_histogram(color='black', alpha=0.4, position='identity') +
scale_fill_manual(values=c('red', 'blue', 'purple')) +
labs(fill='Team', x='Points Scored', y='Count', title='Points Scored by Team') +
theme_classic()
The following tutorials explain how to perform other common tasks in R: