MTA Ridership Project

Team Members

• Haixin Liu
• Hanghai Li

Project Description

This project analyzes MTA Daily Ridership Data to examine COVID-19 recovery patterns across different transit modes in New York City. We explore how subway, bus, and commuter rail ridership has changed over time and compare the recovery rates of different transportation methods.

Research Questions

1. How has MTA ridership recovered since COVID-19 across different transit modes?
2. Which transit modes have recovered faster - subway, bus, or commuter rail?
3. Are there seasonal patterns in the ridership recovery?

Dataset

• Source: MTA Daily Ridership Data
• Updated: Daily

Setup

1. Clone this repository: git clone https://github.com/advanced-computing/bouncing-penguin.git
2. Create virtual environment: python -m venv .venv
3. Activate virtual environment:
   • Mac/Linux: source .venv/bin/activate
   • Windows: .venv\Scripts\activate
4. Install dependencies: pip install -r requirements.txt

Usage

Open mta_ridership_project.ipynb in Jupyter Notebook or VS Code to run the analysis.