Divvy Bike Sharing Analysis for Chicago

Welcome to the Divvy Bike Sharing Analysis project repository! This project dives into the micro-mobility landscape of Chicago, focusing on the operations and utilization of the Divvy bike sharing system. Through exploratory data analysis, Origin-Destination (OD) matrix generation, geographical mapping, and cost-benefit estimation, we aim to gain insights into the dynamics of bike sharing in the Windy City.

Overview This project encompasses various aspects of Divvy bike sharing analysis, including:

• Exploratory Data Analysis (EDA): Understanding the patterns and trends in bike usage over time.
• OD Matrix Generation: Creating origin-destination matrices to analyze trip flows.
• Age Group Analysis: Segmenting users by age to uncover demographic insights.
• Geospatial Mapping: Visualizing bike stations, routes, and usage patterns using QGIS.
• Utilization Percentage Calculation: Determining the efficiency and utilization rate of bikes.
• Cost-Benefit Estimation: Assessing the economic impact and viability of the bike sharing system.

Repository Structure ├── code/ # Contains Python scripts and Jupyter notebooks │ ├── Python file - Chicago Micro-mobility Analysis (Divvy) # Python script for data analysis │ ├── .ipynb - Chicago Micro-mobility Analysis (Divvy) # Jupyter notebook with analysis code and descriptions │ └── Python Codes pdf - Chicago Micro-mobility Analysis (Divvy) # PDF version of the Jupyter notebook ├── report/ # Contains the analysis report │ ├── Report - Chicago Micro-mobility Analysis (Divvy) # Detailed analysis report in PDF format │ └── ... ├── LICENSE # License information for the project └── README.md # Detailed project overview, setup instructions, and usage guidelines

Getting Started To explore the analysis conducted in this project, follow these steps:

1. Clone this repository to your local machine.
2. Navigate to the code/ directory to access the analysis scripts and notebooks.
3. Run the notebooks to replicate the analysis or modify the code to suit your needs.
4. Refer to the reports/ directory for detailed documentation and analysis reports.
5. Explore the maps/ directory for geospatial visualizations generated using QGIS in the report.

Contributing Contributions to this project are welcome! If you have any ideas for improvements, additional analysis, or bug fixes, feel free to open an issue or submit a pull request.