R for Data Science
by Garrett Grolemund, Hadley Wickham
Publisher: O'Reilly Media 2016
Number of pages: 522
This book will teach you how to do data science with R: You'll learn how to get your data into R, get it into the most useful structure, transform it, visualise it and model it. In this book, you will find a practicum of skills for data science.
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by Norman Matloff - UC Davis
This book is for those who wish to write code in R, as opposed to those who use R mainly for a sequence of separate, discrete statistical operations. The reader's level of programming background may range from professional to novice.
by Vincent Zoonekynd
Contents: Introduction to R; Programming in R; From Data to Graphics; Customizing graphics; Factorial methods; Clustering; Probability Distributions; Estimators and Statistical Tests; Regression; Other regressions; Regression Problems; etc.
by Patrick Burns - Burns Statistics
If you don't know of 'The R Inferno', this revised edition is a book-length (intermediate level) explanation of a few trouble spots when using the R language. If you are using R and you think you're in hell, this is a map for you.
by Hadley Wickham
The book is designed primarily for R users who want to improve their programming skills and understanding of the language. It should also be useful for programmers coming to R from other languages, as it explains some of R's quirks...