I received a hardback copy of Tufte’s The Visual Display of Quantitative Information from my wife for Christmas, and amidst all the holiday celebrations and family visits, I didn’t get a chance to sit down with it until today. Having finally done so, however, I inadvertently consumed nearly the entire volume in a single sitting.
If you haven’t heard of him, Ed Tufte is regarded as something of a messiah to Data visualization. I had never actually read any of his written works, though I had knowingly inherited many of his stylistic preferences by proxy of his other disciples. Writ large, I found the book to be largely devoid of surprises: Tufte’s style is more-or-less what one might expect Tufte’s style to be. Data visualization is good for circumstances in which tables are cumbersome, and bad for circumstances in which tables are more succinct. Relational graphics (in which multivariate data is presented) are king, though maps and time-series plots are also critically important. Visually misleading or distracting coloration (e.g. cross-hatching) is bad. Don’t lie with statistical graphics.
All of these are good and correct pieces of advice. If any of them isn’t obvious to you, then the book is nothing short of critical reading for you. Given Tufte’s messianic status, I have some trepidation about reviewing Tufte critically. Never-the-less, I found that some of his sensibilities don’t match my own, and the divergence is sometime dramatic.
Tufte’s grand vision of clean, information-dense visualizations stands at odds with some (contested) empirical evidence. Tufte violates his own vendetta against “chart junk” (a now-common term which he coined in this book at its first printing) by proposing slight modifications to example graphics drawn from print sources, which would adorn those graphs with suggestions for intuitions that precisely meet most definitions of chart junk.
What’s worse, however, is when Tufte moves too far in the opposite direction. Rather than propose we make common plot types (like box-and-whisker, for example), he proposes we can represent the same data using far less “ink” by simply erasing the box and placing a dot at the median. While this is a perfectly adequate solution for the attentive consumer (I would be willing to present graphics like this in a journal article, for example), he goes further to advocate replacing the entire plot with a straight line, having the middle inter-quartile ranges offset by a pixel, and an absent point to represent the median. I find this damn near impossible to read under most circumstances, and shudder to think of asking my consumers to interpret such things.
This highly reductive principle is not without its virtues. In fact, I would venture to say that it is vastly better than damaging. Consider his discourse on scatterplots. Scatterplots are perhaps the most important type of plot a person can learn to interpret, being among the simplest presentation of the most complex bivariate data. Consider this example:
Here we see a number of Tufte’s innovations at work. Note the axes: they are given the same treatment as Tufte recommends for a boxplot. The pixel-offset notwithstanding, I think this is a considerable improvement. It leverages the axes to display information about each variable’s distribution. This is also conveyed by the points replicated outside the range of the irrelevant axis.
It seems to me that Tufte was writing predominantly for an audience of statisticians and designers whose graphics would be consumed via some print media. To this perspective, he discusses at length the visualization hygiene of a variety of print media outlets. It seems he failed to predict the massive data-consumption transition from print-based to screen-based, and has subsequently failed to update either his opinions or his written work accordingly. (The book was published in 1983, and the second edition in 2001.)
Even so, my thinking on statistical graphic design has changed from reading this book, and I expect that will be reflected in my graphs in the future. So, squabbles aside, it was a wonderful read, and I highly recommend it.