Add line for average per group using ggplot2 package in R - GeeksforGeeks

03 Dec, 2021
In this article, we will discuss how to add a line for average per group in a scatter plot in the R Programming Language.
In the R Language, we can do so by creating a mean vector by using the group_by() and summarise() function. Then we can use that mean vector along with the geom_hline() function of the ggplot2 package to create a line by the mean point colored by the group.
To create a mean vector from the data frame,
Syntax:
mean <- df %>% 
group_by( <categorical-variable> ) %>% 
summarise( mean_val = mean( <quantitative-variable> )
Arguments:
df: determines the data frame to be used.
<categorical-variable>: determines the variable that is used to divide data into groups.
<quantitative-variable>: determines the variable whose mean is to be found.
This expression creates a vector with two columns i.e. <categorical-variable> and the mean that stores mean by category. Now, we will use this mean vector with the geom_hline() function to add a horizontal line at the mean/average of data colored by categorical variable.
Syntax:
plot + geom_hline( mean_df, aes( yintercept, col )
Arguments:
mean_df: determines the data frame that contains mean information.
yintercept: determines the variable mean column in dataframe.
col: determines the categorical variable by which line has to be colored.
Example 1:
Here in this example, we have created a scatter plot colored by a categorical variable. Then we have added a line colored by the same variable that goes through the mean of that category of data.
R
# load library tidyverselibrary(tidyverse) # create dataframedf <- data.frame(    group=factor(rep(c("category1", "category2","category3"),                        each=100)),    y=round(c(rnorm(100, mean=65, sd=5),                  rnorm(100, mean=85, sd=5),                 rnorm(100, mean=105, sd=5))),    x=rnorm(300)) # create mean by groupmean <- df%>% group_by(group)%>%summarise(mean_val=mean(y)) # create ggplot scatter plot# add horizontal line overlay at mean using geom_hline()ggplot(data = df, aes(x= x, y=y)) +geom_point(aes(colour = group)) +geom_hline(data= mean, aes(yintercept = mean_val,col=group))
Output:
 
Example 2:
In this example, we have created a scatter plot colored by a categorical variable. Then we have added a line colored by the same variable that goes through the mean of that category of data. We have also added a facet_grid() to convert this plot into a facet plot to better visualize the data through a categorical variable.
R
# load library tidyverselibrary(tidyverse) # create dataframedf <- data.frame(    group=factor(rep(c("category1", "category2","category3"),                        each=100)),    y=round(c(rnorm(100, mean=65, sd=5),                  rnorm(100, mean=55, sd=5),                 rnorm(100, mean=60, sd=5))),    x=rnorm(300)) # create mean by groupmean <- df%>% group_by(group)%>%summarise(mean_val=mean(y)) # create ggplot scatter plot# add horizontal line overlay at mean using geom_hline()# divide plot in facet using function facet_grid()ggplot(data = df, aes(x= x, y=y)) +geom_point(aes(colour = group)) +geom_hline(data= mean, aes(yintercept = mean_val,col=group))+facet_grid(~group)
Output:
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