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How to find the mean of all columns by group in R?
To find the mean of all columns by group, we can use summarise_all function along with mean function after defining the groups with group_by. For example, if we have a data frame called df that contains a grouping column say G and some numerical columns then we can find the mean of all columns by values in grouping column by using the below given command −
df%>%group_by(G)%>%summarise_all("mean")
Example 1
Following snippet creates a sample data frame −
Grp<-sample(LETTERS[1:4],20,replace=TRUE) Score1<-sample(1:50,20) Score2<-sample(1:50,20) Score3<-sample(1:50,20) df1<-data.frame(Grp,Score1,Score2,Score3) df1
The following dataframe is created −
Grp Score1 Score2 Score3 1 C 2 1 46 2 C 39 25 21 3 C 25 6 10 4 A 5 8 25 5 A 37 23 17 6 D 4 21 39 7 B 33 40 31 8 C 28 44 3 9 B 40 50 8 10 B 10 49 14 11 B 27 45 42 12 B 45 7 5 13 C 26 34 28 14 C 31 19 12 15 A 29 46 38 16 A 24 38 48 17 A 21 12 22 18 B 1 9 35 19 A 23 20 20 20 B 50 27 9
To load dplyr package and find the mean of all columns by Grp column, add the following code to the above snippet −
library(dplyr)
df1%>%group_by(Grp)%>%summarise_all("mean")
# A tibble: 4 x 4
Outpu
If you execute all the above given snippets as a single program, it generates the following output: −
Grp Score1 Score2 Score3 <chr> <dbl> <dbl> <dbl> 1 A 23.2 24.5 28.3 2 B 29.4 32.4 20.6 3 C 25.2 21.5 20 4 D 4 21 39
Example 2
Following snippet creates a sample data frame −
Level<-sample(c("First","Second","Third"),20,replace=TRUE)
Price1<-rpois(20,8)
Price2<-rpois(20,8)
Price3<-rpois(20,8)
df2<-data.frame(Level,Price1,Price2,Price3)
df2
The following dataframe is created −
Level Price1 Price2 Price3 1 First 11 12 5 2 First 8 6 5 3 First 5 16 6 4 Second 9 11 9 5 Second 12 12 11 6 Second 5 10 8 7 First 7 6 9 8 First 10 6 11 9 Second 4 9 8 10 First 5 9 5 11 Third 14 6 8 12 Third 4 13 11 13 Second 3 8 5 14 Second 8 3 8 15 Second 6 10 10 16 Second 10 3 9 17 First 8 8 5 18 First 6 3 11 19 Third 5 10 9 20 Third 10 11 10
To find the mean of all columns by Level column, add the following code to the above snippet −
df2%>%group_by(Level)%>%summarise_all("mean")
# A tibble: 3 x 4
Output
If you execute all the above given snippets as a single program, it generates the following output: −
Level Price1 Price2 Price3 <chr> <dbl> <dbl> <dbl> 1 First 7.5 8.25 7.12 2 Second 7.12 8.25 8.5 3 Third 8.25 10 9.5
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