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US County Electoral Map – Land Area vs Population

Posted In: Maps | Voting
county election map 2020

County-level Election Results from 2020 and 2016

The map has been updated to include the latest 2020 results and also adds the option to color the circles by the win margin rather than just looking at the winner.
Click here to view a visualization that looks more explicitly at the correlation between population density and votes by county.
This interactive map shows the election results by county and you can display the size of counties based on their land area or population size.

Previously, I created a map (cartogram) that showed the state by state electoral results from the Presidential Election by scaling the size of the states based on their electoral votes. The idea for that map was that by portraying a state as Red or Blue, your eye naturally attempts to determine which color has a greater share of the total. On a normal election map, Red states dominate, especially because a number of larger, less populated states happen to vote Republican. That cartogram changed the size of the states so that large states with low population, and thus low electoral votes tended to shrink in size, while smaller states with moderate to larger populations tended to grow in size. Thus, when your eyes attempt to discern which color prevails, the comparison is more accurate and attempts to replicate the relative ratio of electoral votes for each side.

This map looks at the 2020 and 2016 presidential election results, county by county. An interesting thing to note is that this view is even more heavily dominated by the color red, for the same reasons. Less densely populated counties tend to vote republican, while higher density, typically smaller counties tend to vote for democrats. As a result, the blue counties tend to be the smaller ones so blue is visually less represented than it should be based on vote totals. More than 75% of the land area is red, when looking at the map based on land areas, while shifting to the population view only about 46% of the map is red. Neither of these percentages is exactly correct because each county is colored fully red or blue and don’t take into account that some counties are won by a large percentage and some are essentially tied. However, the population number is certainly closer to reality as Trump won about 48.8% of the votes that went to either Trump or Clinton.

Instructions

This tool should be relatively straightforward to use. Just click around and play with it.
The map has a few different options for display:

  • Hide Circles – just shows the county map
  • Show land circles – where the area of the circle matches the area of the county itself, though obviously shaped like a circle. The counties are colored red or blue depending on whether Trump or Biden (in 2020) or Clinton (in 2016) won more votes in that county.
  • Show population circles – where the area of the circle matches the relative population of the county itself. More populated counties will grow larger while less populated counties will shrink. The counties are colored red or blue depending on whether Trump or Biden or Clinton won more votes in that county.
  • Selecting the No County Overlap checkbox will spread out all of the circles so you can see them all. The total displayed area of the county circles is the same in either land and population view, though if the circles are overlapping, you may see less total colors.
  • Selecting the Color by Margin checkbox will color the each county circle by the amount that a candidate won the county. If the vote margin is small, the county will be colored light blue or red, whereas if a county strongly favors one candidate, it will be colored darker red or blue.

Visualization notes

This was my second attempt at using d3 to generate visualizations. I typically use leaflet to do web-based mapping but I wanted the power of d3 which has functions for the circles to prevent overlapping. This map was inspired by Karim Douieb’s cool visualization of 2016 election results. I modified it in a number of different ways to try to make it more interactive and useful.

This visualization does not actually simulate the collisions between the circles on your browser. It is a bit computationally taxing and causes my computer fan to turn on after awhile. So instead I ran the simulation on my computer and recorded the coordinates for where each circle ended up for each category. Then your browser is simply using d3 transitions to shift positions and sizes of the circles between each of the maps, which is simpler, though with 3142 counties, it can still tax the computer occasionally.

Data and Tools
County level election data for 2016 is from MIT Election Lab. The 2020 county level data is downloaded from the New York Times county election data API and processed using a python script. Population data used is for 2018. The visualization was created using d3 javascript visualization library.

Sizing the States Based On Electoral Votes

Posted In: Maps | Voting

Electoral Vote maps give more visual power to states with large areas but few electoral votes



This map shows the electoral outcome of the 2016 and 2020 US Presidential Election and is color coded red if the state was won by Donald Trump (R) and blue if the state was won by Hilary Clinton or Joe Biden. When looking at the map, red states tend to be larger in area than blue states, but also generally have lower populations. This gives a misleading impression that the electoral share is “redder” than it actually is. For 2016, we can see that Trump won 306 electoral votes or (57% of the total electoral votes), but the map is shaded such that 73% of the area of the US is colored red. Similarly, Clinton won 232 electoral votes, but the map is shaded such that only 27% of the map is colored blue. For 2020, we can see that Biden won 306 electoral votes or (57% of the total electoral votes), but the map is shaded such that 38% of the area of the US is colored blue. Trump won 232 electoral votes, but the map is shaded such that 62% of the map is colored red.

The map shrinks the states with low electoral votes relative to its area and increases the size of states with large numbers of electoral votes relative to its area. On average blue states grow as they are under-represented visually, while red states tend to shrink quite a bit because they are over-represented visually. Alaska is the state that shrinks the most and DC and New Jersey are the areas that grow the most in the new map.

Here’s another map I made that looks at the 2016 and 2020 Presidential Election by County and shows the size of each county by land area or population.

I think this gives a more accurate picture of how the states voted because it also gives a sense of the relative weight of those states votes.

Data and Tools:
Data on electoral votes is from Wikipedia. The map was made using the leaflet open source mapping library. Data was compiled and calculations on resizing states were made using javascript.

Re-sizing The Electoral Map

Demographic Characteristics of US Voters (2016)

Posted In: Voting

If you need to register to vote, please visit Rock the Vote to get registered in your state.

US politics has more than a few issues, which have been highlighted by the current situation in Washington DC. The protests and greater political awareness from high school students and young adults is a positive sign for democracy, but it needs to be accompanied by increased rates of voting from this demographic. I thought it would be interesting to explore rates of voting in the US across different demographic groups (age, education, income, race). This data is from the 2016 US presidential election.

Total eligible US voting population was about 224 million in 2016 and the overall rate of voting among this population was 61.4%.

The first graph shows the distribution by age. As we can see, the rate of registration and voting increases with age. It is hard to engage young people to be interested in voting but hopefully they will do so in greater numbers this upcoming election.

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