The choropleth problem

Before a reader draws me up short on Monday’s link to an interactive map showing explosive growth of unemployment in the US, I should acknowledge the choropleth problem. James Fallows introduced the issue, and the word, in a blog post about the same map Tuesday.

800px-ElectoralCollege2000-Large-BushRed-GoreBlue-thumb-240x160-30593The problem is that geography does not equal population. A choropleth map depicting social trends (unemployment or election results) can mislead if its geographical units (states or provinces) vary widely in population. (The word derives from Greek terms for “area/region” + “multiply.”) Fallows gives the example of the razor thin 2004 US presidential election, in which the Democratic candidate outpolled the Republican, but a state-by-state choropleth gives the impression of a Republican landslide, because lower density Republican states take up most of the room. Maps that resolve to a county-by-county level (as opposed to state-by-state or province-by-province) greatly reduce but do not eliminate the distortion.

US_Presidential_Election_County_Level_Cartogram_240

Cartograms are maps that attempt to solve the choropleth problem by distorting their geographical units to reflect the numerical value being measured. The county-by-county cartogram of the same election (at left) distorts boundaries but reflects the results more accurately. More herehere, and here. My earlier, much-complained about post about altitude maps depicting crime in San Francisco, relied on a special category of choropleth known to cartobuffs as a prism map.