This project explores bike-share usage patterns between member and casual users by analyzing Divvy trip data from 2019 Q1 to 2020 Q1.
The analysis was conducted using R, with data visualizations created in using Python and Tableau.
Key insights focus on ride duration, usage distribution by day of week, and weekend preferences.