Groupby Count in R

Groupby count in R can be accomplished by aggregate() or group_by() function of dplyr package. Groupby count 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 count the number of occurrences within a group using aggregate() function in R.  Let’s see how to

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

Groupby count 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 count of single column in R:

Method 1:

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

# Groupby count of single column

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

so the grouped dataframe will be

Method 2: groupby using dplyr

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

library(dplyr)
df1 %>% group_by(State) %>% summarise(count_sales = n())

so the grouped dataframe will be

Groupby count of multiple column in R:

Method 1:

aggregate() function which is grouped by “State” and “Name”, along with function length is mentioned as shown below

# Groupby count of multiple columns

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

so the grouped dataframe will be

Method 2: groupby using dplyr

group_by() function along with n() is used to count the number of occurrences of the group in R. group_by() function takes “State” and “Name” column as argument and groups by these two columns and summarise() uses n() function to find count of a sales.

library(dplyr)
df1 %>% group_by(State,Name) %>% summarise(count_sales = n())

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

For further understanding of group by count() function in R using dplyr one can refer the dplyr documentation

Related Topics:

• Groupby maximum in R
• Groupby minimum in R
• Groupby mean in R
• Groupby sum 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