Often you may want to calculate the mean by group in R. There are three methods you can use to do so:
Method 1: Use base R.
aggregate(df$col_to_aggregate, list(df$col_to_group_by), FUN=mean) Method 2: Use the dplyr() package.
library(dplyr)
df %>%
group_by(col_to_group_by) %>%
summarise_at(vars(col_to_aggregate), list(name = mean))
Method 3: Use the data.table package.
library(data.table)
dt[ ,list(mean=mean(col_to_aggregate)), by=col_to_group_by]
The following examples show how to use each of these methods in practice.
Method 1: Calculate Mean by Group Using Base R
The following code shows how to use the aggregate() function from base R to calculate the mean points scored by team in the following data frame:
#create data frame
df #view data frame
df
team pts rebs
1 a 5 8
2 a 8 8
3 b 14 9
4 b 18 3
5 b 5 8
6 c 7 7
7 c 7 4
#find mean points scored by team
aggregate(df$pts, list(df$team), FUN=mean)
Group.1 x
1 a 6.50000
2 b 12.33333
3 c 7.00000
Method 2: Calculate Mean by Group Using dplyr
The following code shows how to use the group_by() and summarise_at() functions from the dplyr package to calculate the mean points scored by team in the following data frame:
library(dplyr) #create data frame df #find mean points scored by team df %>% group_by(team) %>% summarise_at(vars(pts), list(name = mean)) # A tibble: 3 x 2 team name1 a 6.5 2 b 12.3 3 c 7
Method 3: Calculate Mean by Group Using data.table
The following code shows how to calculate the mean points scored by team in the following data frame:
library(data.table) #create data frame df #convert data frame to data table setDT(df) #find mean points scored by team df[ ,list(mean=mean(pts)), by=team] team mean 1: a 6.50000 2: b 12.33333 3: c 7.00000
Notice that all three methods return identical results.
Related: A Complete Guide to the mean Function in R
Additional Resources
How to Calculate the Sum by Group in R
How to Calculate Quantiles by Group in R