How to Use extract() Function in R

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The extract() function from the tidyr package in R is “used to extract multiple values from a single column into multiple columns.”

Syntax

extract(data, col, into, regex, remove = TRUE, convert = FALSE)

Parameters

  1. data: The data frame.
  2. col: The column name you want to extract values from.
  3. into: A vector of column names you want to create.
  4. regex: A regular expression that defines how to extract values.
  5. remove: If TRUE, remove the column that you are extracting values from. If FALSE, keep the original column.
  6. convert: If TRUE, will automatically convert the extracted values into the appropriate type (numeric, integer, etc.). If FALSE, the new columns will be of type character.

Example 1: Extracting First Name and Last Name

library(tidyr)

# Sample data
df <- data.frame(id = 1:3, full_name = c(
  "Alice Brown",
  "Bob Smith", "Charlie Johnson"
))

# Use extract() to split the full_name column
df <- df %>%
  extract(full_name,
  into = c("first_name", "last_name"),
  regex = "(\\w+) (\\w+)"
)

print(df)

Output

Extracting First Name and Last Name in R

Example 2: Extracting Area Code and Phone Number

Imagine you have phone numbers in the format “(AreaCode) PhoneNumber,” and you want to extract the area code and phone number into separate columns.

library(tidyr)

# Sample data
df <- data.frame(id = 1:3, phone = c(
   "(123) 456-7890",
   "(987) 654-3210", "(555) 777-8888"
))

# Use extract() to split the phone column
df <- df %>%
  extract(phone,
  into = c("area_code", "phone_number"),
  regex = "\\((\\d{3})\\) (\\d{3}-\\d{4})"
)

print(df)

Output

Extracting Area Code and Phone Number

That’s it!

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