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Why not use a choropleth map in your analytics panel

Most examples of data-associated maps use shapes with colored outlines and fill to delineate political or geographical boundaries. This type of map is called a “Choropleth map” and certainly has the most significant visual effect on users.

Incredibly, if you use choropleth maps (or intend to use them because you think they’re pretty), you’re probably doing it wrong.

When not to use a choropleth (or polygon) map

First, it is essential to note that there are two preferred approaches to displaying quantitative information on a map: variations in color intensity or size, or intensity and size.

The map of filled polygons below demonstrates the outcome of the 2012 US election. In blue, the states where Obama won, and in red, Romney.

The result of the election we all know: The elected candidate was Obama (coloured in blue).

But this is not a conclusion that can be drawn from the map, because there are more red areas than blue areas; This leads us to believe that it was Romney who won.

In reality, the big confusion is that, when working with colored polygons, it is the area of the filled shape that jumps out at us.

States like Montana (470,000 votes) and Wyoming (250,000 votes) geographically occupy a large area of the map, but represent very little when compared to much smaller states in area like New York (7 million votes) and Maryland (2.5 million votes).

Our eyes perceive larger areas than smaller areas, even if they are exactly the same color.

How to best use the polygon map

To correct the distortion created by the example above, a possible improvement would be to work with gradients: the higher the number of votes, the stronger the color shade (either blue or red, depending on who won that state).

Still, the area of each state causes our eyes to become confused.

The best alternative would be to work with circles on the map, varying color and size, so actual performance becomes clear (in this example it means a reflection on the number of votes and who won) at each dot on the map.

Qlik Sense offers a few tricks on how to build a clean and easy-to-read map. These are:

  • Don’t use the Google Maps-like “satellite view”: it brings too much detail and can get in the way of making sense of the map
  • Customize the map colours and remove all excess labels and information
  • When drawing circles (the data), avoid internal gradient styles: always use solid colors, preferably with transparency, allowing you to see overlapping points on the map

When should we use a polygon map?

As we said, in most cases, the map with circles will work best. But there are cases where polygon maps are more suitable:

  • When the area and geographic position are critical to understanding the visualization, such as in an agricultural map that shows areas planted, harvested, productivity in these areas, etc.

If you want to learn more about this topic, below are some recommended contents:

The Atlantic – You Learn Something Every Day: “Choropleth”

Introduction to Geographical Data Visualization

Take Care of your Choropleth Maps

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