How to Modify ggplot2 Barplot Color in R (2 Examples)
On this page you’ll learn how to modify the color of a ggplot2 barchart in the R programming language.
Setting up the Examples
data(iris) # Loading example data head(iris) # Sepal.Length Sepal.Width Petal.Length Petal.Width Species # 1 5.1 3.5 1.4 0.2 setosa # 2 4.9 3.0 1.4 0.2 setosa # 3 4.7 3.2 1.3 0.2 setosa # 4 4.6 3.1 1.5 0.2 setosa # 5 5.0 3.6 1.4 0.2 setosa # 6 5.4 3.9 1.7 0.4 setosa |
data(iris) # Loading example data head(iris) # Sepal.Length Sepal.Width Petal.Length Petal.Width Species # 1 5.1 3.5 1.4 0.2 setosa # 2 4.9 3.0 1.4 0.2 setosa # 3 4.7 3.2 1.3 0.2 setosa # 4 4.6 3.1 1.5 0.2 setosa # 5 5.0 3.6 1.4 0.2 setosa # 6 5.4 3.9 1.7 0.4 setosa
install.packages("ggplot2") # Install & load ggplot2 package library("ggplot2") |
install.packages("ggplot2") # Install & load ggplot2 package library("ggplot2")
ggplot(iris, # Draw basic ggplot2 barchart aes(x = Species, y = Sepal.Length)) + geom_bar(stat = "identity") |
ggplot(iris, # Draw basic ggplot2 barchart aes(x = Species, y = Sepal.Length)) + geom_bar(stat = "identity")
Example 1: Create ggplot2 Barchart with Default Color Palette
ggplot(iris, # Barchart with the default colors of ggplot2 aes(x = Species, y = Sepal.Length, fill = Species)) + geom_bar(stat = "identity") |
ggplot(iris, # Barchart with the default colors of ggplot2 aes(x = Species, y = Sepal.Length, fill = Species)) + geom_bar(stat = "identity")
Example 2: Create ggplot2 Barchart with User-Defined Color Palette
ggplot(iris, # Manually defined color palette aes(x = Species, y = Sepal.Length, fill = Species)) + geom_bar(stat = "identity") + scale_fill_manual(values = c("setosa" = "purple", "versicolor" = "yellow", "virginica" = "brown")) |
ggplot(iris, # Manually defined color palette aes(x = Species, y = Sepal.Length, fill = Species)) + geom_bar(stat = "identity") + scale_fill_manual(values = c("setosa" = "purple", "versicolor" = "yellow", "virginica" = "brown"))
Related Articles
In the following, you may find some further resources on topics such as ggplot2, factors, and plot legends.