Uber Ride Request Analysis — Python

Overview

EDA on Uber ride request data to understand trip patterns, demand spikes, cancellation rates, and supply-demand gaps.

Problem Statement

Ride-hailing platforms need to understand demand patterns to optimize driver allocation and reduce cancellations.

Tools Used

• Python (Pandas, NumPy, Matplotlib, Seaborn)
• Jupyter Notebook

Key Findings

• Identified peak demand hours and high-cancellation time slots
• Analyzed supply-demand gap by pickup location and time
• Found patterns in trip completion vs cancellation rates

How to Run

pip install pandas numpy matplotlib seaborn jupyter notebook Uber_Analysis.ipynb S