{"id":1010,"date":"2026-10-23T17:32:18","date_gmt":"2026-10-23T17:32:18","guid":{"rendered":"http:\/\/jfdi-blog-what-is-a-choropleth-map"},"modified":"2026-10-23T17:32:18","modified_gmt":"2026-10-23T17:32:18","slug":"what-is-a-choropleth-map","status":"publish","type":"post","link":"https:\/\/jfdi.pro\/blog\/what-is-a-choropleth-map\/","title":{"rendered":"What is a choropleth map, and when does it mislead?"},"content":{"rendered":"\n

A choropleth map shades each area, such as a country, state or council, according to a value, with darker colours usually meaning more. It’s the most common kind of data map. It works well for rates<\/strong> (per person, per km\u00b2, percentages) and badly for totals<\/strong>, because big areas look important just for being big.<\/p>\n\n\n\n

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Make a choropleth map<\/a><\/div>\n<\/div>\n\n\n\n

Where the name comes from<\/h2>\n\n\n\n

The word comes from the Greek choros<\/em> (area) and plethos<\/em> (multitude). The geographer John Kirtland Wright coined it in 1938, but the idea is much older: Baron Pierre Charles Dupin drew a map of France in 1826 shading each d\u00e9partement by access to basic education, usually counted as the first choropleth (Wikipedia<\/a>).<\/p>\n\n\n\n

Mistake 1: mapping totals<\/h2>\n\n\n\n

Shade a world map by total population and China and India are darkest, which is true but tells you nothing a list wouldn’t. Shade it by people per km\u00b2 and you see where people are actually crowded: Bangladesh, the Netherlands, Singapore, Rwanda.<\/p>\n\n\n\n

\"The
Left: total population, which mostly shows which countries are big. Right: people per km\u00b2, which shows where people are crowded.<\/figcaption><\/figure>\n\n\n\n

Totals are what statisticians call extensive<\/em> variables: they grow with the size of the area. Rates are intensive<\/em>: they don’t. A choropleth should almost always show a rate. Skipping this step is one of the most common mistakes in data maps; it made some COVID-19 dashboards misleading.<\/p>\n\n\n\n

If what you really want to show is a total, use sized dots<\/strong> instead: one circle per area, its size set by the value. Readers judge a total by the size of a circle much better than by a shade of colour.<\/p>\n\n\n\n

The JFDI map maker<\/a> checks for this. If a column looks like a total (it rises and falls with population, or it’s called something like Total<\/em>, Number<\/em> or Deaths<\/em>), it suggests showing it per million people, per km\u00b2, or as sized dots. You can still keep it as it is.<\/p>\n\n\n\n

Mistake 2: big areas shout<\/h2>\n\n\n\n

Even with a rate, every area is filled with one flat colour, so a large area looks like it carries more weight than a small one with the same value. Russia, Canada and the US Mountain West dominate maps because they’re big. Ten cities with high values can be invisible next to one empty county with a slightly lower one.<\/p>\n\n\n\n

Ways to soften this:<\/p>\n\n\n\n