R and Data Science Books

We often discuss R books we have used to learn R or find helpful for specific aspects of R (statistics, data science, or programming/coding).

Please feel free to add your favorite and often recommended R, statistics, and data science books.

Learning R

Hands-On Programming with R: Write Your Own Functions and Simulations by Garrett Grolemund O’Reilly link
R for Everyone: Advanced Analytics and Graphics by Jared P Lander Amazon link
A First Course in Statistical Programming 2nd Edition by W John Braun & Duncan J Murdoch (The second edition was released July 8, 2016) 2nd Edition Amazon link 1st Edition Amazon link

R Cookbook by Paul Teetor O’Reilly link
R Graphics Cookbook: Practical Recipes for Visualizing Data by Winston Chang The R Graphics Cookbook is an excellent resource for learning how to make awesome plots with ggplot2 along with helpful topics for experienced ggplot2 users. O’Reilly link book’s website

The Art of R Programming: A Tour of Statistical Software Design by Norman Matloff O’Reilly link
R Packages: Organize, Test, Document, and Share Your Code by Hadley Wickham O’Reilly link book’s website
- R Packages is an excellent introduction and resource for building your own packages and focuses on using the RStudio integrated development environment (IDE).

Data Mashups in R: A Case Study in Real-World Data Analysis by Jeffrey M Stanton book’s website (free PDF)
Data Mashups in R: A Case Study in Real-World Data Analysis by Jeremy Leipzig & Xiao-Yi Li O’Reilly link
Doing Data Science: Straight Talk from the Frontline by Cathy O’Neil & Rachel Schutt O’Reilly link
R for Data Science by Garrett Grolemund & Hadley Wickham To be published by O’Reilly in November 2016. O’Reilly link book’s website
The Book of R: A First Course in Programming and Statistics by Tilman M. Davies No Starch link
97 Things Every Programmer Should Know edited by Kevlin Henney O’Reilly link