Chapter 6 R Learning Resources
A rich and responsive consellation of print and online information, explanation, guidance, and discussion make up the lively and growing R universe. Help is available at any time — you just have to know where to find it.
6.1 Books On R
- Learn R : 12 Free Books and Online Resources
- Practical Data Science With R
- R in Action, Second Edition
- R For Data Science by Hadley Wickham
- R for Everyone by Jared Lander
- Teach Yourself R In 24 Hours
- The R Series | CRC Press Online
6.1.1 Online R Books
- bookdown: Authoring Books With RMarkdown by Yihui Xie
- bookdown.org: R books made with bookdown
- Data Visualization by Kieran Healy
- Efficient R programming by Colin Gillespie & Robin Lovelace
- Happy Git and GitHub for the useR by Jenny Bryan & Others
- R For Data Science by Hadley Wickham
- R packages by Hadley Wickham
- Text Mining with R by Julia Silge and David Robinson
6.1.2 WikiBooks on R
6.2 R Blogs
6.2.1 Aggregation Sites
6.2.2 Corporate/NGO
6.3 R Tutorials
- Awesome-R: A curated list | GitHub
- Data Visualization
- Getting Started | RStudio Support
- How to get started with Data Science using R | R-bloggers
- Implementation of the Matplolib ‘viridis’ color map in R | GitHub
- Learn R, Python & Data Science Online | DataCamp
- Quick list of useful R packages | RStudio Support
- Quick R | DataCamp
- R Package Management Tools
- R-Courses | R-Exercises
- Start here to learn R! | R-Exercises
- Try R | Code School
- Tutorials for learning R | R-bloggers
- UBC STAT 545
- Using R | Working With Data Series
6.4 R Discussion Forums
6.5 R Mailing Lists
6.6 R Podcasts
If you’re into listening to podcasts, there are many great podcasts about R, Data Science, and Artificial Intelligence. Here are some:
- Not So Standard Deviations
- DataFramed
- The R Podcast
- This Week in Machine Learning and AI
- The Microsoft Research Podcast
- Bombshell
- Marketplace
- Revolutions
Collected from: A few podcast recommendations | R-bloggers