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Visualize This Isbn:978-0-470-9448-2 © 2011 Nathan Yau, Published by: Wiley Publishing, 10475 Crosspoint Boulevard, Indianapolis, IN 46256 Author: Nathan Yau, cover Price $39.99, 358 pages

Returning from a trip, I was very pleased to see a review copy of Visualize This waiting for me. The author, Nathan Yau has a great web site, FlowingData which I have been following for some time. I enjoy the site a lot and consider it to be one of the best sites for data display and inspiration.

This book is not for beginners who are not interested in getting their hands dirty with code and cleaning data. If however, you have done the basics, and maybe a bit more than the basics with Excel and want to explore the next level up, then this book is for you.

Visualize This is quite different from many of the other books that I have read on visualization in a good way. The author comprehensively explains how he approaches the task of coming up with useful concepts for data display and then shows you how to do it yourself. He immediately points out that "basic" data display can, and most often is, done using Microsoft Excel. Happily, we have little of that here. The tools of choice are Python (a popular programming language available on all platforms), and R (a sophisticated open source and free data statistics package), coupled with Adobe Illustrator, (a fairly expensive product from Adobe). He also highlights the use of Google Refine, a fairly new tool from Google for cleaning up messy data. This is probably the first time I have seen this useful tool mentioned in print, as opposed to seeing it on the web. The author does mention a number of commercial and open source alternative tools but the bulk of the step by step examples use, Python R and Illustrator.

I was very happy to see the concentration on these specific tools as I have been learning Python and R for a while now, and have Illustrator available (and have used it a bit) as well as the free alternative, Inkscape, which the author also references.

Throughout the book there is a useful survey of other tools, both open source and commercial for obtaining, formatting, and displaying data. There are a number that I have not yet explored. So this book serves as an excellent resource.

Inclusions of specific instructional material with real data and readily available tools sets this book apart.

The book is clearly the product of someone who has thought deeply about the process of producing useful visualizations. The chapter organization echo the suggested processes:

1. Chapter 1 — Telling Stories with Data
2. Chapter 2 — Handling Data
3. Chapter 3 — Choosing Tools to Visualize Data
4. Chapter 4 — Visualizing Patterns over Time
5. Chapter 5 — Visualizing Proportions
6. Chapter 6 — Visualizing Relationships
7. Chapter 7 — Spotting Differences
8. Chapter 8 — Visualizing Spatial Relationships
9. Chapter 9 — Designing with a Purpose

In short, the book belongs on the bookshelf of anyone who is interested in the subject of data visualization beyond the basic level. It has a permanent spot on my reference shelf.