What is the Mutate function for R programming?

How To Use Mutate() for Data Frames, Data Tables, and Matrices in Data Models

A few dependencies in a given language achieve workhorse status — a “go-to” consideration when you first create a model. The dplyr library contains that workhorse for R programming — mutate(). Learning its value is a great way to get into data exploration and tailor your data to modeling needs.

The mutate() function is designed to help the user add or delete a column to an object without changing the other columns. Mutate is a useful way of adding a column of data in which field values are derived from the elements. In most programming scripts, you will see mutate() used in conjunction with a couple of functions to update the elements within a matrix, a data table, or a data frame.

In this post will cover how you can use the mutate function to add new details to the data in your R object. Learning this makes your data model more useful and representative of the observations you want in the model columns.

How the Mutate() Function Works

First, let’s look at how the mutate function typically works within R programming.

Mutate is used when you want to develop additional columns for an object without discarding the original columns. There are many instances when a piped function can return just the calculated result, but not keep the original column. That can be…