This is a comprehensive guide to using R for data science, covering data import, cleaning, manipulation, visualization, and modeling.

R for Data Science by Garrett Grolemund and Hadley Wickham

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A First Course in Programming and Statistics. This book is a great introduction to R for beginners, covering the basics of R programming as well as statistical concepts.

The Book of R by Tilman M. Davies

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This book provides a gentle introduction to R for those with no prior programming experience.

R For Dummies by Andie Foulquier

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This book teaches you how to use R to perform statistical analysis.

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Discovering Statistics Using R by Andy Field, Jeremy Miles, and Zoë Field

A Tour of Statistical Software Design. This book delves into the design and philosophy of R, helping you to become a more proficient R programmer.

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The Art of R Programming by Norman Matloff

Advanced Analytics and Graphics. This book is a great resource for those who are already familiar with the basics of R and want to learn more advanced techniques.

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R for Everyone by Jared P. Lander

Expert techniques for predictive modeling, 3rd Edition. This book is a practical guide to using R for machine learning.

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Machine Learning with R by Brett Lantz

Proven Recipes for Data Analysis, Statistics, and Graphics. This book is a collection of solutions to common R programming problems.

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R Cookbook by Paul Teetor

Proven Recipes for Data Analysis, Statistics, and Graphics. This book is a collection of solutions to common R programming problems.

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R in Action by Robert I. Kabacoff

This book is a reference guide for advanced R users.

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Advanced R by Hadley Wickham