Resources

These are resources I think are useful.

Books

R for Data Science (2e)
Hadley Wickham, Mine Cetinkaya-Rundel & Garrett Grolemund
Whenever someone asks me how to get started with learning R programming, I always point them here.

R Graphics Cookbook, 2nd edition
Winston Chang
This book focuses on R’s plotting capabilities, primarily through the ggplot2 library. I used this resource when I made the intentional decision to sit down and learn how to code plots in R. It’s a cookbook meant to cover the possible situations you may encounter when plotting data, so it isn’t too comprehensive. I didn’t have really any programming experience before I started reading this book.

Functional Programming
Sara Altman, Bill Behrman, Hadley Wickham A practical introduction functional programming in the tidyverse.

ggplot2: Elegant Graphics for Data Analysis
Hadley Wickham
This is the comprehensive resource for ggplot2, explained in through detail by Hadley Wickham, the author of several other key R data science package libraries.

Geocomputation with R
Robin Lovelace, Jakub Nowosad and Jannes Muenchow
Learn how to turn R into a GIS by using the simple features (sf) package.

Blogs and Projects

FlowingData
Nathan Yau, Ph.D
Well-renown statistician and data visualization artist shares his work (also offers membership that includes tutorials and other learning materials).

Nicola Rennie, a data visualization specialist.

Statistics Globe
Joachim Schork
A comprehensive statistics resource for R and Python.

R Graph Gallery
Yan Holtz
The “most extensive compilation of R-generated graphs” found on the internet, it contains over 400 examples of over 50 different plot types primarily focusing on R and ggplot2, with some base R plotting as well.

Julia Silge releases YouTube videos along with each blog post, which are very straightforward and pragmatic analyses

Outsider Data Science
Art Steinmetz
A former Wall Street CEO shares his data stories with R. Lot’s of different analyses all with reproducible code.