Exploratory Data Analysis with R
by Roger D. Peng
Publisher: Leanpub 2016
Number of pages: 208
This book teaches you to use R to effectively visualize and explore complex datasets. Exploratory data analysis is a key part of the data science process because it allows you to sharpen your question and refine your modeling strategies.
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by Colin Gillespie, Robin Lovelace - O'Reilly
The book is about increasing the amount of work you can do with R in a given amount of time. It's about both computational and programmer efficiency. It's for anyone who uses R and who wants to make their use of R more reproducible and faster.
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...