Repositories are the places where all the packages we install in the R environment are stored. Well, every package you install must be stored somewhere, isn’t it? The same way your mobile applications are stored in RAM or your computer programs are stored on a C directory etc. In other words, we can make a statement that a package in R is a way in which you can manage, organize your work in a structured manner, and if needed, could share with others. If you developed a code for doing any task in R which includes different functions of your own and data sets, you can create a package of your own. In fact, you can add a package of your own to R as well. The best thing about R is we can always add a package of our own since it is an open-source language, a lot of users add packages every now and then. In R, we have packages that are a compilation of different functions, procedures, and sample data sets that allow the user to deal with different tasks with ease. If you are new to the field of R Programming, I would recommend you to first go through and get used to this beautiful programming language through the article An Introduction to R Programming. Through this article, we will go through the packages, how to load, install, as well as manage them and so much more. ![]() A user has access for more than 15000 packages in R (this number gets increased every now and then, as users add packages of their own every year) at their fingertips and there is nothing from the field of data science these packages can’t handle in R. Packages allow the user to manipulate almost any data into a way they want. Packages in R programming are one of those fancy things that makes this programming language a go-to tool for data scientists and machine learning engineers.
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