**R in a Nutshell: 2 ^{nd} Edition**

*Joseph Adler*

(O’Reilly, paperback – Kindle)

(O’Reilly, paperback – Kindle)

**Attention, statisticians**, data scientists, data journalists, mathematicians, graphics specialists, and others who use the R programming language. Joseph Adler has updated his popular “desktop quick reference guide” to R.

If you aren’t familiar with R, it is a “free software environment for statistical computing and graphics,” according to the R-Project website. Some of the world’s biggest corporations and news organizations are now using R. But there also are numerous ways individual users can work with R, including using it inside Microsoft Excel by running RExcel.

**The new edition** offers some nice improvements over the 2009 first edition, but it is *not* a full-scale rewrite. After all, R itself generally doesn’t change much from one release to the next.

Here’s what *is* new in the new edition:

- New information on ggplot2 and using R with Hadoop.
- Formatting changes to make the code examples easier to read.
- Plotting chapters have been grouped together.
- “Minor updates.” These “reflect changes in R 2.14 and R 2.15.
- New sections offering how-to information on “useful tools for manipulating data in R , such as plyr and reshape.

**The author says** that while his 699-page book “is designed to be a concise guide to R,” it is “not intended to be a book about statistics or an exhaustive guide to R.”

Chapter 3, however, provides a friendly “short R tutorial” with plenty of basic examples. And Chapter 5 presents a helpful “Overview of the R Language.” The book’s other chapters are packed with code examples, illustrations, and well-written explanations, as well.

*R in a Nutshell***’s chapters** are organized into six parts:

- Part I – R Basics
- Part II – The R Language
- Part III – Working with Data
- Part IV – Data Visualization
- Part V – Statistics with R
- Part VI – Additional Topics (including using r with Hadoop)

Whether you are: (1) new to R, (2) trying to land a job where R skills are required, (3) working on projects that could benefit from R’s excellent statistical and graphics capabilities, or (4) an old hand at R, you should have this updated “desktop quick reference” manual on hand.

— *Si Dunn*