Exploring Various Visualization Methods using Voting Data, D3, and Cartography
When I find free time from making visualizations for customers, I oftentimes find myself having the urge to test out different visualization techniques using different techonology. Yes, it is true! I make geo-visualizations for fun on the side during my free time!
This particular side project focused on the 2024 US Presidential Election turnout at the state level, since states are ultimately what provide the votes from the US Electoral College. The three different visualizations I explored were:
- A static, purely dataviz approach.
- An interactive map approach, created with javascript, d3, python
- An interactive dataviz version of the static charts, created with javascript, d3, etc.
As with most geo-visualizations, I dove deep into statistical analysis to uncover the fascinating stories hidden in the pure raw dataset.
The 2024 Election turnout was lower overall when compared with 2020. These three different visualizations explore the same dataset. The data comes from US Election Project, from which I conducted further statistical analyses to identify the difference in turnout from 2020 to 2024 per each state, and the difference from the national average per each state. Only a handful of states increased in voter turnout, and each of them was a "swing state." If provided more time on this topic, I presume that the campaigns' frequent visits to swing states is partially the reason for the higher turnout.
The three visualizations that I created to view this dataset demonstrate how widely charts can vary to showcase the same data. This is the power of data visualization and mapping. You can also view a live interactive tablet experience of this project on my Instagram.
