Visualizations experts says it’s generally a bad idea to put two different vertical axes on a single graph (see Dual-Scaled Axes in Graphs — Are They Ever the Best Solution? [PDF]) since it invites comparison of data on different scales. However, the treatment is still popular because of the two-in-one information density, and the distortion can be overcome with careful reading.
In the worse case, though, two completely different scales are carefully transformed to almost line up and suggest correlation. An insidious example from a few years ago was the presidential popularity versus price of gas graphs, about which one writer believes show that there’s “clearly a correlation.”
It does look like a correlation, but that’s only because the scales have been transformed to follow the same long-term path, which could be done to any two generally linear data series. There are a couple related spikes for the September 11 attacks and the Iraq War start which our eyes quickly pick up on, but otherwise the local ups and downs don’t match too well. These graphs disappeared shortly afterwards when the two trends obviously diverged (gas prices got better but Bush ratings didn’t).
What I really don’t understand, though, is this next example on employment data from My Budget 360.
I’ve never seen a dual-scaled graph where both scales were the same units and approximate range. What’s the point? It shifted the intersection point a little, but not enough to affect the thesis of the article. It does exaggerate the climb of the blue line (leisure employment). I can’t tell if this one is intentional distortion or just carelessness.