Some time ago, I showed how a column or bar chart could display a table of data more effectively than four pie charts (or a donut chart) in Column Chart to Replace Multiple Pie Charts. I showed how to build a panel chart to plot the same data in How to Build a 2×2 Panel Chart. In this post I’ll demonstrate why donut charts are such an awful way to try to present data.
This is the data used to make the donut chart above, and it’s served us for several other exercises. Rows add up to 100%.
Here again is the donut chart. You can compare values by comparing the included angles, except that only Engr1 and Mktg2 have a common baseline for all points in those categories. If you consider consider the Mktg1 (blue) sections. Three of the four have values between 19.7% and 20.0%. Without consulting the table above, it’s mighty hard to tell which doesn’t fall within that range.
Of course, we could apply data labels that display the values, but to make them fit, some have to be rotated. In this chart I was lucky, because I could stick to horizontal or vertical orientations, and not any of the pixel-squashing inclinations in between.
It’s still hard to remember which concentric arc refers to which series. Let’s change the labels to show series names. Okay, that’s better, but now I can’t remember the percentages.
The dialog lets us add both to our label, in fact, we could also add the categories from the legend. But the labels are already overcrowded. I suppose if we wanted to, we could find a package that lets us wrap the labels around an arc, but I’m glad Excel doesn’t offer that option. But at least we have all the data visible in the chart that was in the original table of data, only not as easy to read.
Donuts, an Exploded View
I’ve pivoted the data so all values are in one column. I’ve also calculated the area of each segment, with a scaling factor that conveniently equals 100 for the hole in the center. The innermost arc has a total area of 300 (that is, three times the area of the central hole), the second 500, the third 700, and the outermost 900. If you’ve been listening to me for a while (I mean months, not just this post), you can guess where this is going.
To start this analysis I had to explode the donut chart. Quick, call Dundas, a new chart type! This was easier than I had expected: I copied the donut as a picture in Excel, pasted onto a PowerPoint slide, and ungrouped twice. Then I dragged the pieces into position.
Then I arranged the segments in order of ascending value from top to bottom. As you can see by eyeballing the pieces, or by looking at the Area column or dot plot in the accompanying sorted table, the area jumps around a lot as the value monotonically increases. If a measure such as area is to be a reliable indicator of value, both measure and value should increase monotonically and proportionally.
Here is the same set of building blocks, this time sorted by area. We can tell from the table, but not from the arcs themselves, that value jumps up and down a lot as area increases.
Let’s compare the donut’s area-value lack of correlation above with the area-value characteristics of a bar chart. This is the data and chart from Column Chart to Replace Multiple Pie Charts.
Here I’ve removed the gaps between clusters and inserted a narrow white strip between adjacent bars. I’ve put labels in the bars so the legend isn’t necessary to identify anything.
Then I sorted the values and rearranged the bars accordingly. The bars are sorted by value and by length. Since each bar has the same thickness, they are also sorted by area.
Which shows the better correlation between value and measure of that value?