Is data visualization worth paying for? In some quarters, this may be a controversial question.
If you are having doubts, just look at some examples of great visualization. This week, the NYT team brings us a wonderful example. The story is about whether dogs feel jealousy. Researchers have dog owners play with (a) a stuffed toy shaped like a dog (b) a Jack-o-lantern and (c) a book; and they measured several behavior that are suggestive of jealousy, such as barking or pushing/touching the owner.
This is how the researchers presented their findings in PLOS:
And this is how the same chart showed up in NYT:
Same data. Same grouped column format. Completely different effect on the readers.
Let's see what the NYT team did to the original, roughly in order of impact:
- Added a line above the legend, explaining that the colors represent different experimental conditions
- Re-ordered the behavior by their average prevalence from left to right
- Added little cartoons to make the chart more fun to look at
- Added colors and removed moire patterns (a Tufte pet peeve)
- Changed the vertical scale from 0 to 1 (scientific) to 0-100
- Reduced the number of tick marks on the vertical scale (this is smart because the researchers observed only about 30 dogs so only very large differences are of practical value)
- Clarified certain category details, e.g. Snapping became "bite or snap at object"
- Removed technical details of p-values, not important to NYT readers
Even simple charts illustrating simple data can be done well or done poorly.