I have a confession: I’m not really a very good data designer. Okay, I’m pretty good at many parts of information design, but when it comes to visualizing hundreds or even thousands of data points and creating a beautiful and effective visualization, it’s fairly likely you’ll find me with my head down on my desk crying like a 4 year old.
The incredible data visualizations that you’ll find at The New York Times or Information is Beautiful or Visualizing.org make me insanely jealous. And so, I couldn’t wait to get my copy of Nathan Yau’s just-published guide to this whole mysterious world.
Nathan is a contributor to one of the pre-eminent sites on this topic, Flowing Data. I’ve been a fan and reader of both for a while.
While a number of other books have addressed data visualization, the ones I have read have mostly been concerned with the end products. Most are more coffee table book than how-to. Visualize This, on the other hand, may be the first true handbook for how to technically create so many of these interesting charts and graphs.
The reader is taken step by step through the creation of numerous styles and categories of visualization. Sprinkled throughout are solid tips on design, statistics and other resources for those interested in this field. The book is written with a good sense of humor and practicality, and it rarely feels academic.
But, this isn’t to say that the material is easy to digest…
To be honest, I didn’t anticipate how technical this book was going to be. It wasn’t long into the book before Nathan started talking code. Code, as in Python, PHP, Javascript, HTML and his favorite, an open source program simply called “R.” From the descriptions, even a “program” like R still requires writing and pasting in lines of code to create charts. Don’t look for a user-friendly GUI. This is not your father’s spreadsheet program.
And speaking of Excel…well, there’s just not a whole lot spoken of it here. Despite the fact that many (but certainly not all) of the charts discussed can be created at least initially in Excel, and despite the fact that included in the book is a Flowing Data user survey showing that most (31%) of readers use Excel to visualize data, Microsoft’s program is largely ignored after a perfunctory introduction. The how-to’s in every chapter take the user through creating bar charts in R and donut charts in a coding toolkit called Protovis (wasn’t that the software company in War Games?) The introduction to the latter begins with, “The first thing you do is create an HTML page…” All this for a donut chart which is essentially a pie chart with a hole in the middle?
Perhaps the problem I have is not with the book’s decision to ignore more user-friendly solutions, but the fact that there are no powerful one stop shop user-friendly software solutions for data visualization. Even if one insists that I am just intimidated by coding (true), Nathan still explains that he imports almost all of his coded visualizations into Adobe Illustrator in the end to make them look good from a design standpoint. So clearly, all these software solutions only get you halfway there.
Perhaps someone will create the Adobe Photoshop or Final Cut Pro of data visualization one day. But until that time, anyone serious about playing in this space must have this book for the very detailed step by step instructions found within.
I really am a fan of Nathan and his work, but this is a book for a determined data designer who has the patience and drive to learn multiple new software and programming tools. My feeling is that this is an investment too involved for most graphic designers or for the average civilian who often presents data.
nice post