Table of Contents
The aggregate() function in R is used to calculate summary statistics (such as means, medians, counts, etc.) for data grouped by one or more variables. It takes three arguments: an input vector or data frame, a grouping variable or variables, and an aggregate function. The result is a data frame with the summary statistics for each group.
The aggregate() function in R can be used to calculate summary statistics for a dataset.
This function uses the following basic syntax:
aggregate(x, by, FUN)
where:
- x: A variable to aggregate
- by: A list of variables to group by
- FUN: The summary statistic to compute
The following examples show how to use this function in practice with the following data frame in R:
#create data frame df <- data.frame(team=c('A', 'A', 'A', 'B', 'B', 'B'), position=c('G', 'G', 'F', 'G', 'F', 'F'), points=c(99, 90, 86, 88, 95, 99), assists=c(33, 28, 31, 39, 34, 23), rebounds=c(30, 28, 24, 24, 28, 33)) #view data frame df team position points assists rebounds 1 A G 99 33 30 2 A G 90 28 28 3 A F 86 31 24 4 B G 88 39 24 5 B F 95 34 28 6 B F 99 23 33
Example 1: Aggregate Mean by Group
The following code shows how to use the aggregate() function to calculate the mean number of points scored by team:
#find mean points by team
aggregate(df$points, by=list(df$team), FUN=mean)
Group.1 x
1 A 91.66667
2 B 94.00000
This tells us:
- Players on team A scored an average of 91.67 points per game.
- Players on team B scored an average of 94 points per game.
Note that you can also change the names of the columns in the output by using the colnames() function:
#find mean points by team agg <- aggregate(df$points, by=list(df$team), FUN=mean) #rename columns in output colnames(agg) <- c('Team', 'Mean_Points') #view output agg Team Mean_Points 1 A 91.66667 2 B 94.00000
Example 2: Aggregate Count by Group
The following code shows how to use the aggregate() function to count the number of players by team:
#count number of players by team
aggregate(df$points, by=list(df$team), FUN=length)
Group.1 x
1 A 3
2 B 3
- Team A has 3 players.
- Team B has 3 players.
Example 3: Aggregate Sum by Group
The following code shows how to use the aggregate() function to calculate the sum of points scored by each team:
#find sum of points scored by team
aggregate(df$points, by=list(df$team), FUN=sum)
Group.1 x
1 A 275
2 B 282
This tells us:
- Team A scored a total of 275 points.
- Team B scored a total of 282 points.
Example 4: Aggregate Multiple Columns
The following code shows how to use the aggregate() function to find the mean number of points scored, grouped by team and position:
#find mean of points scored, grouped by team and position
aggregate(df$points, by=list(df$team, df$position), FUN=mean)
Group.1 Group.2 x
1 A F 86.0
2 B F 97.0
3 A G 94.5
4 B G 88.0
This tells us:
- Players in the ‘F’ position on Team A scored an average of 86 points.
- Players in the ‘F’ position on Team B scored an average of 97 points.
- Players in the ‘G’ position on Team A scored an average of 94.5 points.
- Players in the ‘G’ position on Team B scored an average of 88 points.
The following tutorials explain how to use other common functions in R: