NYT´s blind(ing) spot(s)

The New York Times is probably the most committed of all media outlets worldwide to using data graphics, and I love them for that.  Most of their charts are of high quality; much chartjunk is avoided.

The NYT does have a blind spot.

Or might we say blinding spots?  Its obsession with bubble charts, bubbles fitted in grids, bubbles overlapping, bubbles bursting out of grids is maddening.  Examples abound:

The bubble chart, a particular fancy of professional consultants, is just behind the pie chart as a useless form of data graphics.  Note I said "data graphics", as bubbles have value, albeit limited, in conceptual diagrams. If one only cares about bigger vs smaller, then bubbles are okay. 

If one is concerned about how much bigger, then bubbles are misleading.  Further, bubbles contain no scale, implicit or explicit; one cannot decide if any given bubble is large or small (relative to what?).  Witness the Costco-Walmart chart above: is bubble "17" big or small, the chart gives no reference level, neither a range nor an average.

The human brain works linearly, and we tend to grossly misjudge differences in sizes of bubbles.  Blinding spots indeed!

If you don't believe me, try this test.  In the same section where I found the CEO options chart above, there was an article about the new "Mega" M&M.  See right.

What percent larger is the Mega?   (Click on the question under the image to reveal the answer.) 

 

 

 
 
 
I wish the NYT editors would take note and put an end to these blinding spots!

Thanks Pius for helping with the mouseover image while I´m travelling.

Comments

[John]

Do you have the same objection to bubbles instead of dots on a 2-D scatter plot where bubble size is used to represent a third dimension? I wish I could include an example from my research where , because the data are dense, they work far better than actually trying to show the third dimension.

[derek]

John, it's well known that real quantities are very hard to interpret when shown as areas (see processtrends.com for an example of Cleveland's hierarchy of interpretable graphics). I like to use bubbles as a "bonus" information feature on a scatter graph, but not to make an important point. I always want the important data to be in the first two dimensions of the scatter graph, not the area of the bubbles.

Bubbles are best when they show small integers: it's easy to see the difference between a bubble of area=2.0, and one of area=1.0 or 3.0, especially if the graph comes with a key.

[Jon Peltier]

Bubbles are also effective when they are not used to display a continuous variable, but a variable with discrete values. What comes to mind is the dots representing cities on a map, where a tiny dot is for <10,000 people, the next size is 10-25k, then 25-50k, 50-100, 100-250, etc.

But for gereral use, unless you drastically skew the scale, bubbles are only pretty markers.