The Complete Guide: How to Use the aggregate() Function in R


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

This tells us:

  • 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.

Additional Resources

The following tutorials explain how to use other common functions in R:

How to Use table() Function in R
How to Use gsub() Function in R
How to Use summary() Function in R

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