Writing

Weight Duplexing, Condensed Tabulars, and Multiple Enclosures

More typographic tastiness (see the earlier post) from Hoefler & Frere-Jones with a writeup on Choosing Fonts for Annual Reports. Lots of useful design help and ideas for anyone who works with numbers, whether actual annual reports or (more likely) fighting with Excel and PowerPoint. For instance, using enclosures to frame numbers, or knock them out:

knocking out heaven's door

Another helpful trick is using two weights so that you can avoid placing a line between them:

pick em out of a lineup

Or using a proper condensed face when you have to invite too many of your numerical friends:

squeeze me macaroni

At any rate, I recommend the full article for anyone working with numbers, either for the introduction to setting type (for the non-designers) or a useful reminder of some of the solutions (for those who fret about these things on a regular basis).

Thursday, August 6, 2009 | refine, typography  
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.