P_load function in R – Load Multiple Packages With Ease

Filed Under: R Programming
P Load Function In R

In this tutorial, we’ll talk about the p_load function in R. A package in R is a collection of code, data, and related documentation in a standard way. You can install a package in an R environment for your requirements. R offers a function – “library()” to load the packages. You might have already known about the CRAN, an R packages repository, which includes thousands of packages for various needs. You may be using the library() function to load the packages in R.

But, the worry is, you need to write the library() function for every package that you load. So, R offers a Pacman package, which will help you to load multiple packages at once. The Pacman package offers the “p_load” function in R to load all your packages at once. 


About PACMAN package in R

Pacman package in R is created by a team lead by Tyler Rinker. The main purpose of this package is to provide convenience in installing add-on packages in R.

The Pacman package in R is mainly built on R functions such as install() and library() which helps in installing and loading add-on packages in R.

Pacman package in R offers two main functions to load and unload multiple packages in R. It is very useful when you are dealing with multiple packages for your work.

Let’s see how it works!


Installing and Loading Packages in R

You will be needed multiple packages if you are analyzing, visualizing, and even for model building in R. So, as always you will install the add-on package and load the package in R.

#Install the required packages

install.packages('ggplot2')
install.packages('tidyverse')
install.packages('dplyr')
#Load the packages into R

Library(ggplot2)
library(tidyverse)
library(dplyr)

This is the way that most of us follow when we need to install and load the required packages into R. There is no bad in this.

But, when you need to install and load over 10+ packages, it will be a messy job to install and load each package. This will take some additional minutes and make you raise your eyebrows.

But, worry not. We got the pacman package in R when helps us to install and load multiple packages the same time.


Install PACMAN package

As a first step, you need to install the pacman package in R. Don’t wait, let’s roll!

#Install the required package 

install.packages('pacman')
https://cran.rstudio.com/bin/windows/Rtools/
Installing package into ‘C:/Users/prajw/OneDrive/Documents/R/win-library/4.0’
(as ‘lib’ is unspecified)
also installing the dependency ‘remotes’

trying URL 'https://cran.rstudio.com/bin/windows/contrib/4.0/remotes_2.4.0.zip'
Content type 'application/zip' length 395040 bytes (385 KB)
downloaded 385 KB

trying URL 'https://cran.rstudio.com/bin/windows/contrib/4.0/pacman_0.5.1.zip'
Content type 'application/zip' length 389925 bytes (380 KB)
downloaded 380 KB

package ‘remotes’ successfully unpacked and MD5 sums checked
package ‘pacman’ successfully unpacked and MD5 sums checked

Here comes your confirmation about package installation.


P_load function in R

PACMAN package offers many functions which help you in doing multitasking to save your time. You can explore the functions offered by Pacman by typing “Pacman::” in R.

To install and load multiple packages in R, you need to call p_load function in R.

#Installs and loads specified packages in R

pacman::p_load(ggplot2, dplyr, tidyverse)

The best part of the Pacman is, it will do both installation and loading of the packages which are mentioned by you. It’s super cool right!

I hope you enjoy using Pacman from now. It’s fast, easy, and super cool to use in your works in R.


Conclusion

P_load function in R is a part of the Pacman package. It will allow you to mention the packages you need to install and load into your R environment.

After your input, it takes no time to install and load your favorite packages in your working environment. I enjoy using Pacman in my works and I hope you will get the same feeling on this.

That’s all for now. Happy R!!!

More read: pacman package in R

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