Resources for Getting Started in R

An assortment of resources for learning R, for beginner to advanced users.

I am often asked for resources to help folks get started in R, especially for folks doing some form of self-study. I strongly recommend using R in the RStudio IDE, which makes everything easier.

Beginning at the Beginning

One of my favorites for installing and getting started with R and RStudio, especially for medical data, is the Reproducible Medical Research with R e-book which can be found here. Chapter 2 covers installation of R and RStudio, and Chapter 3 gives a quick overview of some of the cool things you can do with R. Lots of other chapters are helpful, and more chapters are coming.

An Antipodean Starter

Another favorite for beginners is the RYouWithMe? website from R-Ladies Sydney. This website has a lot of good starter tutorials on data cleaning, visualization, and producing output documents with RMarkdown.

Start Tidy (in a Box)

I recommend learning the tidyverse first, as these packages are built to work together, and have a consistent logic. Adding some base R later is important as well.

This is the approach taken by Ted Laderas in Ready for R, which is a self-learning course online.

This is also the approach taken by Mine Cetinkaya-Rundel for the Data Science in a Box website, which has lots of great lessons and tutorials for learning to use R.

The Tutorial Tab

There are a number of interactive tutorials in RStudio. These can be found under the Tutorial tab at the top right - just click on one of these to get started.

A video course

Getting Started with R helps a lot of people get started, and is in a video format.

The Wide (and growing) World of E-Books

Starting out

The R basics book can help get you started.

Just past beginner

Try Hands on Programming with R, aka HOPR

Another late-beginner level book, Modern Dive is a intro Statistics-course focused e-book featuring the tidyverse, which can be found here.

A common reference for “How do I do X in R?” is the R Cookbook.

R for Data Science

Most people really dig in to data science with R4DS.

This is the main data science “textbook” that most people use when digging into R in a serious way. For late beginner to early intermediate users.

There is even an exercises Solution Manual available online.

Brushing up on Stats

If you want to brush up on your statistics while learning R, there are several good resources

• Learning Statistics with R

• OpenIntro Statistics: Labs for R is a companion for the OpenIntro Statistics textbook

More Advanced Topics

1. Rmarkdown - You can get started with Rmarkdown to create many kinds of documents with 2 helpful books - The Definitive Guide and the Rmarkdown Cookbook

2. Graphics - You can see how to do a lot with R graphics with the R Graphics Cookbook. Other good graphics resources include Fundamentals of Data Visualization and Data Vizualization

3. Shiny -You can learn how to make your own web applications in R in the Shiny framework with Mastering Shiny

4. Txt mining - If text mining is your area, consider Text Mining with R.

5. Programming - Efficient R programming helps you develop good coding habits (good for intermediate users)

6. Command Line - If you are using big data on a server, you may need to use R at the Command Line

7. Packages - If you want to build your own R packages, you need the R Packages book.

8. Reproducibility and Version Control - requires tools like Git and Github. You can get started with Happy Git and GitHub for the UseR

9. Advanced R really gets under the hood of R

10. Many, many other field-specific books and resources are compiled and organized in the Big Book of R