Groupby Function in R – group_by is used to group the dataframe in R. Dplyr package in R is provided with group_by() function which groups the dataframe by multiple columns with mean, sum or any other functions.
We will be using iris data to depict the example of group_by() function
library(dplyr) mydata2 <-iris # Groupby function for dataframe in R summarise_at(group_by(mydata2,Species),vars(Sepal.Length),funs(mean(.,na.rm=TRUE)))
Mean of Sepal.Length is grouped by Species variable.
Groupby function in R with dplyr pipe operator %>%:
library(dplyr) mydata2 <-iris # Group by function for dataframe in R using pipe operator mydata2 %>% group_by(Species) %>% summarise_at(vars(Sepal.Length),funs(sum(.,na.rm=TRUE)))
Sum of Sepal.Length is grouped by Species variable with the help of pipe operator (%>%) in dplyr package.
So the output will be
Groupby in R without dplyr using aggregate function:
In this example we will be using aggregate function in R to do group by operation as shown below
mydata2 <-iris # Group by in R using aggregate function aggregate(mydata2$Sepal.Length, by=list(Species=mydata2$Species), FUN=sum)
Sum of Sepal.Length is grouped by Species variable with the help of aggregate function in R