New book review for R in Action: Data Analysis and Graphics with R, by Robert Kabacoff, Manning Publications, 2011, reposted here:
Quite a few texts on R have entered the marketplace over the last few years, so my decision to go with this text about a year ago was based on my survey of a number of reviews others have written for this and other books in this space, along with my personal experience with other Manning publications such as "Spring in Action", "Java Persistence with Hibernate", and "Hadoop in Action". In general, my experience working through this book has been pleasant, so I personally do not understand some of the complaints that other reviewers have made about the content that Kabacoff provides here.
That said, however, be forewarned that as with other texts, you should not expect to find all of your answers about R in this book. In my opinion, Manning publications are typically written in a format that fits well with the agile learning method with which I have grown accustomed during my consulting career. The author introduces topics along the way, sometimes more piecemeal that I would like, but his style forced me to explore other resources for more detail, bringing familiarity to other available resources. The number of plugin statistical packages for R has grown exponentially over the years (there are now over 2500), for example, so no book, not even "R in a Nutshell: A Desktop Quick Reference (Second Edition)", which I purchased recently, should be expected to be a one-stop shop.
This text quickly brought me up to speed with R language basics working with data sets, and introduced me to specifics with regard to R statistical methods and visualizations. Using R 2.15.0 for Windows, starting with the small data sets the author provides with which to run his examples, as well as sample data sets that the R language itself provides, I soon found myself working with larger data sets that the City of Chicago makes publicly available via its website, followed by using R at work. Your comfort level will be greater or lesser depending on your experience working with data.
As someone new to R, but not new to working with data, I especially appreciated the first five chapters that encompass the first of four parts in the book ("Introduction to R", "Creating a Dataset", "Getting Started with Graphs", "Basic Data Management", and "Advanced Data Management"). Like it or not, but as with any language, most data work revolves around first getting it into the correct format. After these first five chapters, the author walks the reader through basic graphs and statistics, followed by intermediate methods such as regression and analysis of variance (ANOVA), and advanced methods such as generalized linear models and more advanced graphics than was covered earlier in the book.