If you’re an avid R user, you probably already know that R has a vast selection of libraries loaded with functions and data sets that can help you achieve your analytical goals. But what if you want to use a library that isn't already included in your version of R? In this guide, we'll take you through the steps you need to follow to load a library in R, so you can start using the latest and greatest tools available.
Determine Which Library to Install
Before we delve into loading a library into R, it’s essential to understand that there are two types of libraries you can install- CRAN and Github. CRAN is the default repository that comes with R, so it's typically easier to use if you’re new to installing libraries in R. Github libraries, on the other hand, offer access to cutting-edge libraries, but require a little more effort to install.
To install a CRAN library, you’ll want to start by running this command in RStudio or your preferred R environment:
install.packages(\"name_of_library\")
You can replace \"name_of_library\" with the name of the library you’re interested in. Note that the library names are case sensitive, so be sure to enter them exactly as they appear in the repository.
Install a Github Library
Installing a Github library is more complicated than installing a CRAN library since you first need to install the devtools package. To install devtools, run this command:
install.packages(\"devtools\")
Once devtools is installed, you can use the following command to install the library from Github:
devtools::install_github(\"github_username/library_name\")
Make sure to replace \"github_username\" with the name of the Github user who created the library and \"library_name\" with the name of the library you’re interested in.
Load a Library in R
Once you’ve successfully installed a library, you’ll want to load it into your R workspace so that you can start using the various functions and datasets it offers. To do that, you can use the library() function:
library(name_of_library)
Make sure to replace \"name_of_library\" with the name of the library you’re interested in.
Conclusion
Now that you know how to install, load, and use both CRAN and Github libraries in R, you can start exploring an even wider range of tools and data to help you achieve your analytical goals. Remember to regularly check for the latest libraries and updates, and don't hesitate to ask for help on various R communities if you run into difficulty loading a library.
"