Examples for Visualizing Data

Source code for the book examples for the folks who have kindly purchased the book (lining my pockets, $1.50 at a time).

Chapter 3 (the US map example).

Chapter 4 (time series with milk, tea, coffee consumption)

Chapter 5 (connections & correlations – salary vs. performance)

Chapter 6 (scatterplot maps – zipdecode)

Chapter 7 (hierarchies, recursion, word treemap, disk space treemap)

Chapter 8 (graph layout adaptation)

These links should cover the bulk of the code. More can be found at the URLs printed in the book, or copy & pasted from Safari online. As I understand it, those who have purchased the book should have access to the online version (see the back cover).

All examples have been tested but if you find errors of any kind (typos, unused variables, profanities in the comments, the usual), please drop me an email and I’ll be happy to fix the code.

Monday, February 4, 2008 | examples, vida  

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.