Now reading: Visualize This

I’ve just read Visualize This by Nathan Yau and you should too.
Before I go and develop why, I’d like to say a few words about the author.

Thank you Nathan!

Nathan started flowingdata in 2007. This wasn’t the first blog on data visualization, and his author wasn’t the best known member of this community. Maintaining the blog wasn’t (and still isn’t) his full-time occupation. Yet flowingdata rose to be the most read data visualization blog, thus making a huge service to us all, bringing this science much needed visibility.
Nathan pulled this off by posting something everyday: original content, fine examples of visualizations, technological advances, tutorials, and so on.

As if that were not enough, the job boards at flowingdata are an invaluable ressources for anyone who seeks to hire and infovis expert… and for experts themselves obviously.

So, for all of this: thank you Nathan!

Visualizing data or visualize this?

One of the first book I read on visualization was Visualizing Data by Ben Fry (not the equally interesting Cleveland book of the same title). Back then I wanted a generic book about good practices on visualization without getting my hands dirty with code. But Visualizing Data is really a book about processing. This is both the greatest limitation and the greatest strength of this book, which will teach you processing through data examples. (I am never happier than in front of an empty processing sketch).

Visualize this!, by contrast, is more agnostic. It has the same ambition to help beginners get past the initial stumbling blocks of visualization, but with a greater variety of tools. Nathan’s favorite approach is to start with R then turn to Illustrator for the win. Yet he covers more tools such as python, protovis or flash.

Nathan doesn’t go very far into the nitty-gritty. Instead, he attempts to make those tools less intimidating, more approachable. Also and perhaps more importantly, the focus of the various chapters is to distill some good ideas and practices on top of the practical examples.

Which lead us to…

Visualize this or Show me the Numbers?

Show me the Numbers by Stephen Few is one the essential books on data visualization. I have said many times that if one should read only one book on charts and tables, it should be this. A few years after reading it, I find its recommendations to be a bit rigid (which its author is not).

For comparison’s sake, here is what Stephen says about pie charts.

Speaking of “difficult to read”, allow me to declare with no further delay that I don’t use pie charts, and I strongly recommend that you abandon them as well. My reason is simple: pie charts communicate poorly. This is a fundamental problem with all types of area graphs but especially with pie charts. Our visual perception is not designed to accurately assign quantitative values to 2-D areas, and we have an even harder time when the third dimension of depth is added.

Now here’s what Nathan has to say on the subject:

Pie charts have developed a stigma for not being as accurate as bar charts or position-based visuals, so some think you should avoid them completely. It’s easier to judge length than it is to judge areas and angles. That doesn’t mean you have to completely avoid them though.

You can use the pie chart without any problems just as long as you know its limitations. It’s simple. Keep your data organized, and don’t put too many wedges on one pie.

The above is fairly representative of the tone of the book, which is less directive, less scary perhaps, than other guides that have been written on the subject. Nathan will point you in the right direction, rather than force you to do things in a certain way (as an aside, the citation of Show me the Numbers is less representative of that book as it is the strongest-voiced recommendation).

Wrapping up

Once you close Visualize this! you won’t be a master of R. But you will be on the good track to become one if you choose to. If you know nothing about visualization it is a comforting way to start as it presents the field in an accessible way. This is arguably the first book to do so. If you know more on visualization there may be a thing for you. I knew nothing on Illustrator for instance, and I also learned things in the first and last chapters. I also appreaciated the more design-oriented approach compared to more technical books.

At the end of this month I will go on vacation. I will leave the book on my desk and it will disappear, like my favorite books on the subject before it. I might find who will have borrowed it from me, but not who will have borrowed it from them… What better fate can I hope for this book?

 

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