The Visual Display of Quantitative Information

Translations:no translations yet

I decided to read it because at the time of reading I had to draw a lot statistical graphs at my work and I had no idea how to do it in a best possible way. I’ve read it and convinced myself even more about facts I already knew:

The book has two main ideas. It’s graphical integrity and data-ink ratio. They could be described in 10 pages or so (including good and bad examples), but the author missed his own points in writing. The writing is verbose (i.e. data-ink ratio is low), most of the examples are of questionable use.

I guess it’s pretty long because Tufte wanted to cover a little bit of history of graphical representation of an information.

One of the best examples of infographics.

Graphical integrity

Graphical integrity is more likely to result if these six principles are followed:


Five principles in the theory of data graphics produce substantial changes in graphical design. The principles apply to many graphics and yield a series of design options through cycles of graphical revision and editing.


Chartunk does not achieve the goals of its propagators. The overwhelming fact of data graphics is that they stand or fall on their content, gracefully displayed. Graphics do not become attractive and interesting through the addition of ornamental hatching and false perspective to a. few bars. Chartjunk can turn bores into disasters, but it can never rescue a thin data set. The best designs (for example, Minard on Napoleon in Russia, Marey’s graphical train schedule, the cancer maps, the Times weather his­tory of New York City, the chronicle of the annual adventures of the Japanese beetle, the new view of the galaxies) are intriguing and curiosity-provoking, drawing the viewer into the wonder of the data, sometimes by narrative power, sometimes by immense detail, and sometimes by elegant presentation of simple but interesting data. But no information, no sense of discovery, no wonder, no substance is generated by charjunk.

Data density and small multiples

High density is usually achieved on maps. Kilobytes of information per square centimeter.

Well-designed small multiples are

Small multiples reflect much of the theory of data graphics:

Aesthetics and technique