Democratic Delegate Scenarios

counter.jpgOne of the chapters that I had to cut from Visualizing Data was about scenarios—building interactive “what if” tools that help you quickly try out several possibilities. This is one of the most useful aspects of dynamic visualization—being able to try out different ideas in a quick way (and safe, as in non-destructive, since Undo is always nearby). Hopefully I’ll be able to cover this sometime soon.

At any rate, one such scenario-building tool is Slate’s Delegate Calculator, where you can drag primitive sliders back and forth and see the possibilities for delegate outcomes for Hillary and Obama.

I’ve seen complaints about its math, but it seems to do an OK job for a big-picture look at the likelihood of different outcomes. Getting the math 100% is impossible (unless you have a far more complicated interface) because the delegate selection process is different in each state. It appears that none of the states wanted to be seen using the same approach as another, and with fifty states going their own way, things got pretty random (Texas: we’ll have a caucus and a primary).

I think that’s enough posting about politics for a bit.

Saturday, March 15, 2008 | election, politics, scenarios  

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.