The “mutate” Function in R

• Package: dplyr

• Purpose: Adds new columns or modifies existing columns in data frames.

• General Class: Data Manipulation

• Required Argument(s):

• .data: A data frame or tibble.

• ...: Expressions that define the new columns.

• Notable Optional Arguments:

• None specific to mutate, but it can be used in combination with other functions from dplyr (e.g., filter, select, etc.).

• Example:

• # Example data for mutating a data frame using dplyr
  library(dplyr)
  
  df <- data.frame(
  ID = 1:5,
  Name = c("Alice", "Bob", "Charlie", "David", "Emma"),
  Age = c(25, 30, 22, 28, 35)
  )
  
  # Add a new column "Age_Group" based on the "Age" column
  mutated_df <- mutate(df, Age_Group = ifelse(Age > 30, "Old", "Young"))
  
  # Display the mutated data frame
  print(mutated_df)

• In this example, the mutate function from the dplyr package is used to add a new column (“Age_Group”) to a data frame (df) based on a condition from an existing column (“Age”). The result is a mutated data frame (mutated_df) with the additional column. Note that you need to have the dplyr package installed and loaded to use the mutate function.