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Creating an R package is easy! Follow along with this Jupyter Notebook tutorial to learn how to develop R packages of your own.

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R Package Dev

A walkthrough in R package development by Spencer Seale

Last revised October 2020

Why you should want to make an R Package

R by itself is a useful programming language. Out of the box it comes packed with functions developed for data manipulation and statistical analysis that users take advantage of regularly. However, what makes R especially powerful is the framework it provides for allowing users to openly create and distribute custom packages. Because of this, thousands of open-source R packages are available for just about any common data science task. But packages can contain functions for anything, seriously anything, check this link out if you need to get your creative juices flowing: https://rpubs.com/dbecker7/StrangeRThings

Installing packages specific to your R-related work is likely something you already do, but you may not know how easy making your own package actually is. By completing this tutorial, you'll be able to quickly build your own package from the ground up and be ushered into the world of package creation, quickly forgetting what source() even does.

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Creating an R package is easy! Follow along with this Jupyter Notebook tutorial to learn how to develop R packages of your own.

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