Trump should ignore this county choropleth map when showing election results
But he won’t because he loves it too much. When Trump invited some reporters to talk about his 100 days in office, he handed out an election map with the results of 2016. According to Reuters accompanied with the words:
Here, you can take that, that’s the final map of the numbers, It’s pretty good, right? The red is obviously us.
The president is known for following the news thoroughly. His poor approval ratings are nothing new for him. He doesn’t like that at all. To me, this seems yet another childish attempt to exaggerate his legitimacy.
Below my analysis of why this map isn’t suited for representing population data. The Mercator map is quite accurate when you want to show where people voted what but not so much how many people voted. I also added a ‘lollipop chart’ of the popular vote results per state to not get lost in the county violence.
So how should election data be represented? Well, physicist Mark Newman of the University of Michigan did quite an impressive attempt.
Or what do you think of the following map by the New York Times?
When showing the popular vote results the following so called dot density map shows actually 1 dot per 1 vote. Yes, a staggering number of 65,844,610 blue democratic dots and 62,979,636 red republican dots.
With this dot per person approach one could ask: Has a new era arrived of REAL Data visualisation?
Meanwhile it’s good to see that news publications are being very creative and precise when representing population data as accurately as possible. The Washington Post wrote an insightful article about this topic with vivid visualisations.
Next you see how each publication is using their own maps. The size of the states represents the number of citizens.
This is a repost and part 5 of the series Data Visualisation Redesigned for the Better.
You can find the code behind the lollipop chart on the Colourful Facts Github repo. For more redesigns and other data journalism/visualisation related articles, go to my blog:
Do you stumble upon a crappy graph? Please let me know! Cheers 🙂
