R is revolutionizing the world of statistical computing. Powerful, flexible, and best of all free, R is now the program of choice for tens of thousands of statisticians. Destined to become an instant classic, R Graphics presents the first complete, authoritative exposition on the R graphical system. Paul Murrell, widely known as the leading expert on R graphics, has developed an in-depth resource that takes nothing for granted and helps both neophyte and seasoned users master the intricacies of R graphics. After an introductory overview of R graphics facilities, the presentation first focuses on the traditional graphics system, showing how to work the traditional functions, describing functions that are available to produce complete plots, and how to customize the details of plots.
The second part of the book describes the grid graphics system - a system unique to R and much more powerful than the traditional system. The author, who was integral in the development of the grid system, shows, starting from a blank page, how it can be used to produce graphical scenes. He also describes how to develop new graphical functions that are easy for others to use and build on. Appendices contain a brief introduction to the R system in general and discuss how the traditional and grid graphics systems can be combined.
Much of the information presented in this book cannot be found anywhere else. Well ahead of the curve, particularly regarding the grid system, R Graphics will have a major impact on the future direction of statistical graphics development.
The author maintains a website with more information.
a lot of insihgts for those of us who need to know R's internals and want a companion to the source.
Also worth a glance by anyone who works with grobs (quantmod users).
Finally, if you're thinking of writing your own plotting software (say you want to add histograms or function plotting to idris or some other new language), the R team has put a _lot_ of work and thought into their graphics library. There might not be a better book to give yourself ideas for that kind of job.
The book provides a good introduction to the R graphics system and gives a very good presentation of the kinds of graphs you can generate using R. This book is definitely not a how-to or cookbook for R graphics though. The book assumes the reader is already familiar with R and the graphics related commands, so there's not much explanation of the short code snippets that go along with the figures. If you're new to R, this book won't show you how to create graphs. It will show you the graphing capabilities of R though and possibly get you interested enough to keep using R.
If you do know R, what this book *will* show you is how to do more complex things with R graphics. Half the book covers the traditional graphics model, while the other half covers the Grid and Trellis graphics models. This will be the interesting part of the book because Grid and Trellis look like they let users create really neat graphs and data representations with R.
I would have liked to see some more complete examples in the book, but at least there's an accompanying website that contains all the code used to generate the graphs and errata for the book. This would be a good addition to an R user's bookshelf.
I don't think I could recommend this to an R novice (Appendix A, "A Brief Introduction to R," does seem reasonable for a beginner but I'm not sure about the rest)... but it's a well-explained and thorough resource for someone with solid R experience already. It helped me solidify some concepts about R graphics and pointed out features of which I hadn't been aware. I'll be coming back to this when I need a refresher on plotting regions, layout, data symbols, etc. The "par" cheatsheets on p.51 and 53 are great. And if you want to extend R using grid graphics, this is the place to start.
Useful book for getting into the fairly complex graphical system of the R Statistical Programming Environment. Definitely not a bed time read. Or, maybe, a great bed time read. Absolutely one for the true science wonk.