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ggplot2 is a powerful data visualization package in R. It provides a wide range of functions to customize the appearance of axis labels, including the ability to rotate them. This can be done by using the “theme()” function in ggplot2, specifying the “axis.text.x” or “axis.text.y” element, and setting the “angle” parameter to the desired angle of rotation. This article provides several examples of how to rotate axis labels in ggplot2.
You can use the following syntax to rotate axis labels in a ggplot2 plot:
p + theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust=1))
The angle controls the angle of the text while vjust and hjust control the vertical and horizontal justification of the text.
The following step-by-step example shows how to use this syntax in practice.
Step 1: Create the Data Frame
First, let’s create a simple data frame:
#create data frame df = data.frame(team=c('The Amazing Amazon Anteaters', 'The Rowdy Racing Raccoons', 'The Crazy Camping Cobras'), points=c(14, 22, 11)) #view data frame df team points 1 The Amazing Amazon Anteaters 14 2 The Rowdy Racing Raccoons 22 3 The Crazy Camping Cobras 11
Step 2: Create a Bar Plot
Next, let’s create a bar plot to visualize the points scored by each team:
library(ggplot2) #create bar plot ggplot(data=df, aes(x=team, y=points)) + geom_bar(stat="identity")
Step 3: Rotate the Axis Labels of the Plot
We can use the following code to rotate the x-axis labels 90 degrees:
library(ggplot2) #create bar plot with axis labels rotated 90 degrees ggplot(data=df, aes(x=team, y=points)) + geom_bar(stat="identity") + theme(axis.text.x = element_text(angle=90, vjust=.5, hjust=1))
Or we can use the following code to rotate the x-axis labels 45 degrees:
library(ggplot2) #create bar plot with axis labels rotated 90 degrees ggplot(data=df, aes(x=team, y=points)) + geom_bar(stat="identity") + theme(axis.text.x = element_text(angle=45, vjust=1, hjust=1))
Depending on the angle you rotate the labels, you may need to adjust the vjust and hjust values to ensure that the labels are close enough to the plot.
The following tutorials explain how to perform other common tasks in ggplot2: