The goal is to analyze the distribution of fuel stations (gas/EV) and registered vehicles in each region across the US, predict suitable locations for gas/charging stations to promote sustainable transportation solutions, and identify states that would benefit from EV policy rebates, with the aim of providing business value to investors of fuel establishments, customers interested in buying EV/gas vehicles, and government policymakers.
SAS Viya, Python, Location Analytics using SAS, Azure Cloud
Very nice topic on an issue bound to attract more attention as more electronic vehicles (EVs) come online. One outstanding question that I have is this: what % of cars use public charging stations - versus ones in the home - and does this vary significantly across the various states? Why does this matter? Well, you'd technically need fewer stations in less densely population urban areas with single family homes (like many places in Seattle) versus densely populated cities like NYC.
I'd also like to hear a bit more about the methodology used to calculate the Folium Map, if you have them. For example, more information on the underlying empirical methodology would be nice.
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