How to use the aggregate method In R Language
Aggregate() method in base R is used to split the data into subsets. It can also be used to compute summary statistics for each of the computed subsets and then return the result in a group by form.
Syntax: aggregate(x, by, FUN)
Arguments :
- x – A list or data frame
- by – The list of the column of the data frame to group by
- FUN – The function to apply to x
The boxplot method in R is used to produce box-and-whisker plot(s) of the specified grouped set of values. The boxplot method in R has the following syntax :
Syntax: boxplot( formula)
Arguments :
- formula – formula, such as y ~ grp, where y is a numeric vector of data values
The boxplot can be customised further to add points and text on the plot.
Syntax: points (x , y , col, pch)
Arguments :
- x ,y – The coordinates of the points to mark
- col – The colour to plot the points with
R
# defining the columns of the data framedata_frame <- data.frame(col1=c(rep("A", 10) , rep("B", 12) , rep("C", 18)), col2=c( sample(2:5, 10 , replace=T) , sample(4:10, 12 , replace=T), sample(1:7, 18 , replace=T)) df_col1 <- list(data_frame$col1) # computing the mean data framedata_mod <- aggregate(data_frame$col2, df_col1, mean)# plotting the boxplotboxplot(data_frame$col2 ~ data_frame$col1) # calculating rows of data_modrow <- nrow(data_mod) # marking the points of the box plotpoints(x = 1:row, y = data_mod$x, col = "red", pch = 14 ) # adding text to the plottext(x = 1:row, y = data_mod$x - 0.15, labels = paste("Mean - ", round(data_mod$x,2)), col = "dark green") |
Output:
How to plot means inside boxplot using ggplot2 in R?
In this article, we are going to see how to plot means inside boxplot using ggplot in R programming language.
A box plot in base R is used to summarise the distribution of a continuous variable. It can also be used to display the mean of each group. Means or medians can also be computed using a boxplot by labeling points.