Summarize Multiple Columns of data.table by Group in R

Last Updated : 23 Sep, 2021

In this article, we will discuss how to summarize multiple columns of data.table by Group in R Programming Language.

Creating table for demonstration:

# load data.table package
library("data.table")

# create data table with 3 columns
# items
# weight and #cost
data <- data.table( items= c("chocos","milk","drinks","drinks",
                             "milk","milk","chocos","milk",
                             "honey","honey"),    
                   
                   weight= c(10,20,34,23,12,45,23,
                             12,34,34),
                   
                   cost=  c(120,345,567,324,112,345,
                            678,100,45,67))

# display
data

Output:

We can summarize the multiple columns in 4 ways:

By finding average
By finding sum
By finding the minimum value
By finding the maximum value

we can do this by using lapply() function

Syntax: datatable[, lapply(.SD, summarizing_function), by = column]

where

datatable is the input data table
lpply() is used to hold two parameters
first parameter is .SD is standard R object
second parameter is an summarizing function that takes summarizing functions to summarize the datatable
by is the name of the column in which data is grouped based on this column

Example 1: R program to summarize the data table by sum and mean value

# load data.table package
library("data.table")

# create data table with 3 columns
# items
# weight and #cost
data <- data.table( items= c("chocos","milk","drinks","drinks",
                             "milk","milk","chocos","milk",
                             "honey","honey"),    
                   
                   weight= c(10,20,34,23,12,45,23,
                             12,34,34),
                   
                   cost=  c(120,345,567,324,112,345,
                            678,100,45,67))


# group by sum with items column
print(data[, lapply(.SD, sum), by = items])

# group by average with items column
print(data[, lapply(.SD, mean), by = items])

Output:

Example 2: R program to summarize data table by minimum and maximum value

# load data.table package
library("data.table")

# create data table with 3 columns
# items weight and #cost
data <- data.table( items= c("chocos","milk","drinks","drinks",
                             "milk","milk","chocos","milk",
                             "honey","honey"),    
                   
                   weight= c(10,20,34,23,12,45,23,
                             12,34,34),
                   
                   cost=  c(120,345,567,324,112,345,
                            678,100,45,67))

# group by minimum  with items column
print(data[, lapply(.SD, min), by = items])

# group by maximum with items column
print(data[, lapply(.SD, max), by = items])