![]() ![]() In the choropleth above, there are many places where you can step over a county border and the political affiliation abruptly changes. Variations in purple are tough to distinguish, and having only a few colors means only a few categories of data to compare.Ĭhoropleths can also create artificial demarcations or give the illusion of boundaries where there are none. This adds more nuance to the data set, but can be difficult to read. In this choropleth, different shades of purple represent counties with varying support for the Republican or Democratic candidate. The choropleth and cartogram above do not address the problem of varied data within counties. (For another example of a cartogram, view PopEd’s cartogram of world population here.) Now it is easier to see how close the election was: red and blue take up more equal space on the map, representing similar amounts of red and blue voters. Counties with smaller populations have been condensed. Counties with greater populations have been stretched out. This cartogram distorts geographic areas based on another factor, in this case, population. In this cartogram map, the states no longer resemble the standard view of the US. By dividing the data into geographic areas rather than population, it’s unclear how many total voters voted for each party. Many blue counties are densely populated, and many red counties were only sparsely populated. Glancing at this map, one could conclude that the Republicans won the presidential election by a landslide: most of the map is red. Red counties voted majority-Republican blue counties voted majority-Democratic. Geographic regions are broken into counties. Understanding limitations can be important for choosing the best type of map for your own data, and for being an informed map-reader.Ĭonsider this choropleth map of voters during the United States presidential election in 2016. While choropleths are useful for telling stories, they can also distort data and be misleading. Spotting Data Distortions in Choropleth Maps Now we’re going to share some of the pitfalls to using choropleth maps to visualize and understand data. You already know the choropleths use color to represent data that is location-specific and can be a useful tool for certain analyses. This post builds on our What is a Choropleth Map post from September 22, 2021. Limitations to Choropleth Maps: A Warning on Misleading Data ![]()
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