Visualize This: The FlowingData Guide to Design, Visualization, and Statistics. R Graphics, Second Edition (Chapman &Hall/CRC The R Series) (9781439831762): Paul Murrell. Review: R Cookbook from O’Reilly. R can be confusing when you're first starting out, especially when you don't have any experience in programming.
There's a lot of documentation online, and package developers do a decent job at providing examples on how to use their work in your code, but that stuff is not always easy to find. It's easy if you know the name of the package or function you're looking for. However, most of the time you just know what you want to do—like sort a data frame or test a regression model—and not the name of a package. The R Cookbook by developer Paul Teetor might be your answer. Overview. Book: The Art of R Programming. R, the favorite computing language of a growing number of statisticians, is friendly enough that you can get a lot done without being an expert programmer, because there are a lot of packages and built-in functions that can take care a lot of the grunt work for you.
Learn how to use a function, prepare your data, and you get some output. However, as you use R more, whether it's for analysis or just for graphics, there comes a point when there isn't a package or function that does exactly what you want. Norman Matloff's Art of R Programming is for those who want to learn to write their own software in R. This is an R programming book that starts from the beginning — running R, vectors, lists — to the more advanced such as simulations, object-oriented programming, and debugging. R Cookbook (O'Reilly Cookbooks) (9780596809157): Paul Teetor. The Art of R Programming: A Tour of Statistical Software Design (9781593273842): Norman Matloff.