Mutate function in R

The mutate() function in R Programming Language is used to add new variables in a data frame which are formed by performing operations on existing variables. It can be used by loading the dplyr library.

Syntax:

mutate(x, expr)

Parameters:

• x: Data Frame
• expr: operation on variables

Types of mutate() Function in R

In R there are five types of main function for mutate that are describe as below. We will use dplyr package in R for all mutate functions. The dplyr library can be installed using the install.packages() function.

install.packages("dplyr")
library(dplyr)

1. mutate() Function in R

The mutate() function in R is used to create new variables or modify existing variables in a data frame without removing any other variables. It allows you to apply transformations or calculations to columns and add the result as new columns or overwrite existing ones.

library(dplyr) 
    
d <- data.frame( name = c("Abhi", "Bhavesh", "Chaman", "Dimri"), 
                age = c(7, 5, 9, 16), 
                ht = c(46, NA, NA, 69), 
                school = c("yes", "yes", "no", "no") ) 

mutate(d, x3 = ht + age) 

Output:

2. transmute() Function in R

The transmute() function in R is used to create new variables or modify existing variables in a data frame, while simultaneously dropping the variables that are not part of the result.

library(dplyr)

d <- data.frame(
  name = c("Abhi", "Bhavesh", "Chaman", "Dimri"),
  age = c(7, 5, 9, 16),
  ht = c(46, NA, NA, 69),
  school = c("yes", "yes", "no", "no")
)

result <- transmute(d,
                    name = name,
                    age_in_months = age * 12,
                    ht,
                    school)

return(result)

Output:

3. mutate_all() Function in R

The mutate_all() function is used to apply a transformation to all variables in a data frame simultaneously.

library(dplyr)

d <- data.frame(
  name = c("Abhi", "Bhavesh", "Chaman", "Dimri"),
  age = c(7, 5, 9, 16),
  ht = c(46, NA, NA, 69),
  school = c("yes", "yes", "no", "no")
)

d_mutate_all <- d %>%
  mutate_all(~ ifelse(is.numeric(.), . * 2, .))

return(d_mutate_all)

Output:

4. mutate_at() Function in R

The mutate_at() function in R is used to apply transformations to specific columns in a data frame, based on a condition, such as column names or positions.

library(dplyr)

d <- data.frame(
  name = c("Abhi", "Bhavesh", "Chaman", "Dimri"),
  age = c(7, 5, 9, 16),
  ht = c(46, NA, NA, 69),
  school = c("yes", "yes", "no", "no")
)

d_mutate_at <- d %>%
  mutate_at(vars(age), ~ .^2)

print(d_mutate_at)

Output:

5. mutate_if() Function in R

The mutate_if() function in R, part of the dplyr package, is used to apply a transformation to variables in a data frame based on a specific condition. It allows you to selectively apply a mutation only to the variables that satisfy the specified condition.

library(dplyr)

d <- data.frame(
  name = c("Abhi", "Bhavesh", "Chaman", "Dimri"),
  age = c(7, 5, 9, 16),
  ht = c(46, NA, NA, 69),
  school = c("yes", "yes", "no", "no")
)

d_mutate_if <- d %>%
  mutate_if(is.numeric, ~ . * 2)

return(d_mutate_if)

Output:

In this article, we explored how to add new variables to a data frame using existing variables in R Programming, with the help of the mutate() function.