Why choropleth maps compare rates, not totals
A choropleth map fills areas—such as counties, states, or countries—with shades that represent a measured value. The key choice is what value to map. If the question is where a condition is most common, the map should usually show a rate or percentage, not the raw number of cases.
A raw count mixes two things: how often something happens and how many people live in the area. A densely populated region may have more cases simply because it has more residents. Dividing the count by the population at risk produces a rate, making it possible to compare places on a more equal basis. For example, the share of residents affected can be more informative than the total number affected when comparing a large city with a small rural county.
What the colors can—and cannot—show
Mapmakers group values into ranges, then assign a shade to each range. Darker colors often indicate higher rates, so readers can spot geographic patterns quickly. But the result depends on the chosen ranges: changing the cutoffs can make the same data look more or less stark. A map’s legend is therefore essential to interpreting its colors.
Even a well-designed choropleth describes regions, not individuals. A county with a high rate does not mean every person there faces the same risk, and broad regions can hide differences within their boundaries. The map is most useful as a first view of where rates differ—not as an explanation of why they differ. It also makes a crucial comparison fairer: a small place can stand out because its rate is high, not merely because a larger population produced a bigger total.
