GTFS-ride is an open standard for storing and sharing fixed-route transit ridership data.

Source code for OST-P/Volpe project exploring estimation of segment-level transit ridership and other measures from GTFS feeds.

MTA Subway Origin-Destination Ridership Estimate for 2023.

Scripts to build and maintain a dataset of Chennai Metro's ridership through time. Inspired by a similar project for Bengaluru's Namma Metro.

EDA and data visualization project exploring the ridership and customer segmentation of Capital Bikeshare data in Washington, D.C.

The study utilizes Multiscale Geographically Weighted Regression (MGWR) to examine how built environment factors affect metro ridership in Chicago.

Time series methods for transit ridership forecasting.

predict starbucks locations, python, R

Clustering NYC subway stations based on their ridership patterns. I identify 4 categories using two axes: amount of ridership and time of use.

Interactive Python Dash dashboard for analyzing campus shuttle ridership trends. Supports data-driven decisions such as adjusting vehicle capacity, modifying service hours, and identifying under- or over-utilized stops through time-based and stop-level analysis.

Urban transport ridership analysis (Chicago vs Philadelphia) — Power BI + Python ETL + stats.

Time series methods for public transit ridership forecasting