| No, but I can give some suggestions. It would help to know what you want to do. First of all, you need to decide if you want a language reference, or an application guide, as R books fall into those two categories. If you have a specific type of work in mind (bio-informatics, data mining, data visualization, ...) I'd say to find a book that focuses on that topic. I haven't looked in a while, but I haven't seen a general R book that I like, anything I suggest there would be guessing on my part. There are plenty of good references on the web. I'd start by looking at the material available from the R web site: R's core manuals [1] are typically correct and reasonable to use. The "Introduction to R" guide will get you up to speed fairly well if you already know another programming language. There is also the contributed documentation [2]. I haven't gone through these, so I can't say much about them, or promise that they are up-to-date. I suspect not, as R develops rapidly. The one reference I can recommend highly is "The R Inferno" by Patrick Burns [3]. This is not a starter guide, but something you read after one. It gives excellent advice on avoiding common pitfalls in R. [1] http://cran.r-project.org/manuals.html [2] http://cran.r-project.org/other-docs.html [3] http://www.burns-stat.com/pages/Tutor/R_inferno.pdf |
So far I could satisfy most of my statistics needs with the function in numpy and scipy but occasionally I need to do something slightly more fancy and R I guess is the way to go.