ggplot2 is an R package for producing statistical, or data, graphics, but it is unlike most other graphics packages because it has a deep underlying grammar. This grammar, based on the Grammar of Graphics (Wilkinson 2005), is composed of a set of independent components that can be composed in many different ways. This makes ggplot2 very powerful because you are not limited to a set of pre-specified graphics, but you can create new graphics that are precisely tailored for your problem. This may sound overwhelming, but because there is a simple set of core principles and very few special cases, ggplot2 is also easy to learn (although it may take a little time to forget your preconceptions from other graphics tools).
Practically, ggplot2 provides beautiful, hassle-free plots, that take care of fiddly details like drawing legends. The plots can be built up iteratively and edited later. A carefully chosen set of defaults means that most of the time you can produce a publication-quality graphic in seconds, but if you do have special formatting requirements, a comprehensive theming system makes it easy to do what you want. Instead of spending time making your graph look pretty, you can focus on creating a graph that best reveals the messages in your data.
The book is accompanied by a new version of ggplot2: version 1.1.0. This includes a number of minor tweaks and improvements, and considerable improvements to the documentation. Coming back to ggplot2 development after a considerable pause has helped me to see many problems that previously escaped notice. ggplot2 1.1.0 (finally!) contains an official extension mechanism so that others can contribute new ggplot2 components in their own packages. This is documented in a new vignette, vignette(“extending-ggplot2”). ggplot2 is now stable, and is unlikely to change much in the future.