These packages can be accessed from the CRAN websiteor directly from R’s repositories.

Nevertheless, because R is an open-source programming language, there are a lot of user-contributed packages available for various purposes and are publicly accessible to anyone. These packages are mounted in a designated folder on your computer and are used for a broad range of computational tasks, such as data management and statistical analysis. Aside from the software itself, the R installation file includes about 30 default or recommended packages, where about seven are loaded into memory immediately once R is launched. This entire process happens automatically and does not require user intervention. Simply put, an R package consists of a series of R functions, such as datasets, support files, and compiled code, packed in a compact and well-defined manner.īasically, these packages are just compressed files that must be unzipped and placed in the right location on your machine before you can use them in R. However if not, you can follow the guide in the link above and get R and RStudio up and running on your operating system before proceeding further with this guide.īut first, let’s clear some air regarding packages in R Understand Package Management In R We will not cover how to install R and RStudio on your computer as I assume you already did that considering. And if we learn to install R packages from the command line, we should also learn how to remove them. We will also look into how package management in R works, install and manage CRAN mirrors as well as package masking for situations when two packages use the same function name. The command syntax to install R packages is install.packages() and we will learn exactly how to use it.

In this lesson, we are going to learn how to install R packages step-by-step from R CRAN repositories as well as GitHub using the install package command.

Rstudio install package