Writing

I Think Somebody Needs A Hug

I tend to avoid reading online comments since they’re either overly negative or overly positive (neither is healthy), but I laughed out loud after happening across this comment from a post about salaryper on the Freakonomics blog at the New York Times site:

How do I become a “data visualization guru?”
Seems like a pretty sweet gig. But you probably need a degree in Useless Plots from Superficial Analysis School.

– Ben D.

No my friend, it takes a Ph.D. in Useless Plots from Superficial Analysis School. (And if you know this guy, please take him out for a drink — I’m concerned he’s been indoors too long.)

Thursday, June 5, 2008 | reviews, salaryper  
Book

Visualizing Data Book CoverVisualizing Data is my 2007 book about computational information design. It covers the path from raw data to how we understand it, detailing how to begin with a set of numbers and produce images or software that lets you view and interact with information. When first published, it was the only book(s) for people who wanted to learn how to actually build a data visualization in code.

The text was published by O’Reilly in December 2007 and can be found at Amazon and elsewhere. Amazon also has an edition for the Kindle, for people who aren’t into the dead tree thing. (Proceeds from Amazon links found on this page are used to pay my web hosting bill.)

Examples for the book can be found here.

The book covers ideas found in my Ph.D. dissertation, which is the basis for Chapter 1. The next chapter is an extremely brief introduction to Processing, which is used for the examples. Next is (chapter 3) is a simple mapping project to place data points on a map of the United States. Of course, the idea is not that lots of people want to visualize data for each of 50 states. Instead, it’s a jumping off point for learning how to lay out data spatially.

The chapters that follow cover six more projects, such as salary vs. performance (Chapter 5), zipdecode (Chapter 6), followed by more advanced topics dealing with trees, treemaps, hierarchies, and recursion (Chapter 7), plus graphs and networks (Chapter 8).

This site is used for follow-up code and writing about related topics.