This project attempts to explore the relationship between Divvy ridership and weather. The weather data was scraped from Wunderground(https://www.wunderground.com/history/) and ridership data isreleased every quarter by Divvy(https://www.divvybikes.com/system-data).
The strongest indicatior of demand is whether the lake effect is in place or not. See my PDF for insights!
I will try to make updates to both the scope and modeling of this project. Organization of files will start to mirror cookiecutter workflow hopefully.