I can’t really remember how I came across this book. I think it was recommended by Amazon. The price was ok (about 31€), at least for a Wiley book, so I just went ahead and bought it. You probably know Nathan Yau from his blog FlowingData where he frequently posts visualizations and interesting infographics.
Overall, the book is quite nice. It starts with some basic discussion about on visualizations in general, stressing the fact that visualizations are an excellent tool to tell the stories behind statistical data. It then goes through some tools, starting with Excel, and then covering tools like R, as well as JavaScript plotting libraries like protovis (now abandoned in favor of D3.js), and several other more specialized libraries, for example, for maps.
The remainder of the book goes through different kinds of visualizations in detail, from timeseries data, scatter plots, maps, etc. Each of the chapters focuses on one tool and show how to get the final plot in great detail.
What I found particularly interesting is that his workflow almost always includes refining the plot in Illustrator to make the graphic more appealing and to add explanations and further labels. This might be nice if you create static visualizations, but if you want to generate dynamic visualizations automatically from data, you’ll have to keep tweaking the original plot until it looks nice enough.
The book is probably too entry level if you already have some experience with data analysis or programming. It tries to require no prior knowledge in programming, although I wonder whether you can really learn how to use R from the examples alone. On the other hand, if you want to do some visualization with maps, for example, it’s nice to have almost complete examples in there.
I also particularly liked the introduction and the final chapter which give a lot of interesting insight on the business of creating visualizations.
Posted by Mikio L. Braun at 2011-08-26 12:20:00 +0000