DMRC project 2024 This project focuses on analyzing the Delhi Metro Rail Network using Python for data processing and Power BI for interactive visualizations. The objective is to derive meaningful insights into ridership trends, peak travel hours, route-wise traffic distribution, and station-wise usage.

Using Python libraries like Pandas, NumPy, Matplotlib, and Seaborn, raw data was cleaned, transformed, and explored. Key findings such as the most and least busy metro lines, variations in ridership during weekdays vs weekends, and usage patterns across different stations were extracted.

The processed data was then visualized in Power BI to create an interactive dashboard showcasing:

Ridership over time

Station-wise footfall

Route heatmaps

Peak hour trends

Line performance comparison

This end-to-end pipeline supports data-driven decision-making for transport planning, peak-hour management, and improving the commuter experience across the Delhi Metro system.