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This is an analysis of the voting in the counties of the United States in the presidential election.
Scroll down to continue.But how? Maybe with a map of the United States...
We can use colors to differentiate who won in each state. If a state voted mostly for Democrats it will be blue, if it voted mostly for Republicans it will be red.
One of the problems with this graphic is that it does not show the individual results of the counties.
By counties the result is different, but also misleading, but it is still far from accurate as it doesn't represent the actual percentage of votes...
Let's add a scale where darker colors represent higher differences, and lighter colors represent smaller differences. However, this is still misleading...
For example, even though and have similar opposing results percent wise, they are very different in terms of population ( vs ).
Another problem with this map is that it shows the results by geographic area, and for example, rural counties have a lot of area but a small population.
Let's replace each county with a circle of the same size to make a more accurate visual comparison.
Another problem, the circles appear on top of each other 🤦🏻♂️...
Let's add a repulsion force that makes each circle try to avoid being on top of another.
We still have the problem that all circles are the same size ☹️. How about we use the size of the circle...
How about we use the area (not the radius) of the circles to represent the total number of voters.
If you want to know the values of each county, move the mouse over the center of the circle.
With this map it is a bit easier to see how the country voted.
For example, it can be seen how larger counties and near the coast tend to vote more for Democrats, while interior counties for Republicans.
With the map it is not so easy to know. (In reality, maps are not the best way to visualize data for most analysis tasks 😉).
Now we have more space to use. But the counties are still located by geographic position, which is no longer necessary.
Removing the geographic position allows us to use the location to encode more information. For example, we can place counties horizontally depending on who the voted more towards...
To differentiate the counties more easily, we can distribute them horizontally by how they voted. We send to the left those who voted more for Democrats and to the right those who voted more for Republicans.
We can use it to divide by regions.
This graphic shows us how each region of the United States voted. Here we can observe, for example, how the New England region tends to vote more for Democrats, versus East South Central which voted more for Republicans. This allows for easier comparison and understanding of the final election results.
We can also change the vertical position to encode the number of voters by population.
Thanks for making it this far, I hope you liked it. If you have any questions or suggestion feel free to reach out via social media, just search for John Alexis Guerra Gómez.
Using data from MIT Election Data and Science Lab
MIT Election Data and Science Lab, 2018, "County Presidential Election Returns 2000-2020", https://doi.org/10.7910/DVN/VOQCHQ, Harvard Dataverse, V13, UNF:6:GILlTHRWH0LbH2TItBsb2w== [fileUNF]
2024 Data from https://github.com/tonmcg/US_County_Level_Election_Results_08-24