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How to Make Cartograms in R

While the reshaped geography doesn’t work all the time, the use of size to show data can be more intuitive in some cases.

Maps are a good way to visualize spatial data, but to maintain geographic accuracy, there are often tradeoffs. For example, a choropleth map, which shades regions by a specified metric, maintains the same shape regardless of the data you color by. Larger regions always take up more space on the screen and smaller regions take up less space.

Cartograms are a response to this challenge by sizing regions to match the data of interest, at the sacrifice of geographic accuracy. This can get messy, as you can imagine, so you’ll have to use your judgement for when and when not to use them.

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About the Author

Nathan Yau is a statistician who works primarily with visualization. He earned his PhD in statistics from UCLA, is the author of two best-selling books — Data Points and Visualize This — and runs FlowingData. Introvert. Likes food. Likes beer.