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How To Show Mean Value in Boxplots with ggplot2?

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In this article, we will discuss how to show mean value in Boxplot with ggplot2 using R programming language.

Firstly, we will create a basic boxplot using the geom_boxplot() function of the ggplot2 package and then do the needful, so that the difference is apparent.

Syntax:

ggplot() + geom_boxplot()

Example: Basic boxplot

R

# load library tidyverse
library(tidyverse)
library(ggplot2)
  
# basic boxplot
ggplot(diamonds, aes(x=cut, y=price)) +
  
# geom_boxplot is used to plot the boxplot
  geom_boxplot()

                    

Output:

In order to show mean values in boxplot using ggplot2, we use the stat_summary() function to compute new summary statistics and add them to the plot. We use stat_summary() function with ggplot() function.

Syntax:

stat_summary(mapping = NULL, data = NULL, geom = “pointrange”, position = “identity”, color=”value”, shape=”value”,…)

Example: Adding mean value to boxplot

R

# load libraries
library(ggplot2)
library(tidyverse)
  
# basic boxplot
ggplot(diamonds, aes(x=cut, y=price)) +
  
# geom_boxplot is used to plot the boxplot
  geom_boxplot() +
  
# stat_summary computes the statistics summary
# fun.y arguments as mean determines that 
# statistical summary will be mean of y-axis
stat_summary(fun.y="mean")

                    

Output:

In the output produced above, the point in the center of the boxplot shows the variation of the mean of the y-axis for each category of data on the x-axis.

We can also change the color and shape of the mean mark using the color and shape parameter of the stat_summary() function. This helps us visualize the data better by distinguishing the mark from other symbols.

Example: Customizing added mean values

R

# load library tidyverse
library(tidyverse)
library(ggplot2)
  
# basic boxplot
ggplot(diamonds, aes(x=cut, y=price)) +
  
# geom_boxplot is used to plot the boxplot
  geom_boxplot() +
  
# stat_summary computes the statistics summary
stat_summary(fun.y="mean",color="red", shape=13)

                    

Output:



Last Updated : 10 Oct, 2021
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