Uber NYC Rider Experience Case Study
Overview
Data-driven analysis of Uber ride performance across NYC zones and rider segments using Python.
Key Insights
- Riders aged 18–22 cancel significantly more often, with a 24 percent cancellation rate compared to the 14.6 percent overall average
- Wait time strongly influences cancellations, particularly in high-demand zones
- The Bronx shows the longest average wait times and highest cancellation rates, highlighting operational supply-demand imbalance
Tools Used
Python, Pandas, Data Visualization
Business Takeaway
The analysis highlights a supply-demand imbalance across NYC zones and suggests a need for operational strategies that reduce rider wait times and improve service reliability in underserved areas.
Project Screenshots (Placeholder)
Add chart or screenshot here (e.g., wait time by zone or cancellation trend)