Groupby sum in R

Groupby sum in R can be accomplished by aggregate() or group_by() function of dplyr package. Groupby sum of multiple column and single column in R is accomplished by multiple ways some among them are group_by() function of dplyr package in R and aggregate() function in R.  Let’s see how to

• Groupby sum of single column in R
• Groupby sum of multiple columns
• Groupby sum using aggregate() function
• Groupby sum using group_by() function.

Groupby sum and its functionality has been pictographically represented as shown below

First let’s create a dataframe

df1= data.frame(Name=c('James','Paul','Richards','Marico','Samantha','Ravi','Raghu','Richards','George','Ema','Samantha','Catherine'),
    State=c('Alaska','California','Texas','North Carolina','California','Texas','Alaska','Texas','North Carolina','Alaska','California','Texas'),
    Sales=c(14,24,31,12,13,7,9,31,18,16,18,14))
df1

df1 will be

Groupby using aggregate() syntax:

Groupby sum of single column in R

Method 1 : using Aggregate ()

Aggregate function along with parameter by – by which it is to be grouped and function sum is mentioned as shown below

# Groupby sum of single column

aggregate(df1$Sales, by=list(df1$State), FUN=sum) 

so the grouped dataframe will be

Method 2: groupby using dplyr

group_by() function takes “state” column as argument  summarise() uses sum() function to find sum of sales.

library(dplyr)
df1 %>% group_by(State) %>% summarise(sum_sales = sum(Sales)) 

so the grouped dataframe with sum of sales calculated will be

Groupby sum of multiple column in R:

Method 1:

Aggregate function which is grouped by state and name, along with function sum is mentioned as shown below

# Groupby sum of multiple columns
aggregate(df1$Sales, by=list(df1$State,df1$Name), FUN=sum) 

so the grouped dataframe will be

Method 2: groupby using dplyr

group_by() function takes “State” and “Name” column as argument and groups by these two columns and summarise() uses sum() function to find sum of a sales.

library(dplyr)
df1 %>% group_by(State,Name) %>% summarise(sum_sales = sum(Sales))

so the grouped dataframe by “State” and “Name” column with aggregated sum of sales will be

For further understanding of group_by() function in R using dplyr one can refer the dplyr documentation.

Related Topics:

• Groupby maximum in R
• Groupby Count in R
• Groupby minimum in R
• Groupby mean in R
• Row wise Standard deviation – row Standard deviation in R dataframe
• Row wise Variance – row Variance in R dataframe
• Row wise median – row median in R dataframe
• Row wise maximum – row max in R dataframe
• Row wise minimum – row min in R dataframe