February talks, and exploratory data analysis using visuals
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Layered donuts have excess fats and oils

Via Twitter, Nicholas S. sent this chart:


It's a layered donut. There isn't much context here except that the chart comes from USDA. Judging from the design, I surmise that the key message is the change in proportion by food groups between 1970 and 2014. I am assuming that these food groups are exhaustive so that it makes sense to put them in a donut chart, with all pieces adding up to 100%.

The following small-multiples line chart conveys most of the information:


The story is the big jump in "Added fats and oils".  In the layered donut, the designer highlighted this by a moire effect, something to be avoided.

Note the parenthetical 2010 next to the Added fats and oils label. The data for all other food groups come from 2014 but the number for the most important category is four years older. The chart would be more compelling if they used 2010 data for everything.

One piece of information is ostensibly absent in the line chart version - the growth in the size of the pie. The total of the data increased about 20% from 1970 to 2014. In theory, the layered donut can convey this growth by the perimeters of the circles. But it doesn't appear that the designer saw this as an important insight since the total area of the outer donut is clearly more than 20% of the area of the inner donut.



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You know where a layered donut chart would be great? The ingredients of the layers of a donut. Filling, dough, frosting. Sugar, fat, sugar, respectively.


I actually rather like the donut. I know it's not canonical, but it does give you both the visual narrative of increase, and the change in the detailed categories.


Alex: There is something about charts with solid color blocks that appeal to our aesthetic sensibility. The issue is that most of these charts can only convey the most basic of information, such as went up-came down. The donut is very tricky because readers are likely to first size up the areas, which means nothing. In these situations, try applying my self-sufficiency test - remove all the data from the chart, and see if you are still happy with it. If yes, then I'd say use it!


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