Dropping Statistics for Knowledge

My favorite part of this week’s Seminar on Innovative Approaches to Turn Statistics into Knowledge (aside from its comically long name) was the presentation from Amanda Cox of The New York Times. She showed three particular projects which are a little further up the complexity scale as compared to a lot of the work from the Times, and much more like the sort of numerical messes that catch my interest. The three serve are also a great cross-section of Amanda’s work with her collaborators, so I’m posting them here. Check ’em out:

“How Different Groups Voted in the 2008 Democratic Presidential Primaries” by Shan Carter and Amanda Cox:

oh hillary

“All of Inflation’s Little Parts” by Matthew Bloch, Shan Carter and Amanda Cox

soap bubble opera

And finally, “Turning a Corner?” which is perhaps the most complicated of the bunch, but gets more interesting as you spend a little more time with it.

just give it some time

Sunday, July 19, 2009 | infographics  

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.