geocrime-stl

A Python utility for cleaning and standardizing St. Louis Metropolitan Police Department (SLMPD) crime data for spatial analysis.

✨ Features

• End-to-End ETL: Fetch, clean, and standardize monthly SLMPD crime data files automatically.
• Spatial Formats: Convert cleaned DataFrames seamlessly into GeoJSON, GeoPackage (GPKG), or CSV.
• Analysis Ready: Access built-in methods for minimal data summarization and visualization.

🌐 Data Source & Disclaimer

This utility programmatically fetches publicly available crime data directly from the St. Louis Metropolitan Police Department (SLMPD) Stats Page.

⚠️ Data Disclaimer & Limitations:

• Availability: This tool relies entirely on the upstream availability and hosting structure of the SLMPD website. If their servers are down or their URL layout changes, the extraction pipeline may fail.
• Data Integrity & Spatial Boundaries: The data processed is strictly "as-is" from the published monthly files. To ensure high data quality for spatial analysis, this utility applies two strict filtering constraints:
  1. Temporal Filtering: Because the SLMPD frequently updates historical records retroactively, this utility isolates and preserves only the records belonging to the target month.
  2. Spatial Clipping: Records containing invalid, malformed, or erroneous latitude/longitude coordinates that plot completely outside the official St. Louis city boundaries are automatically dropped.
• Project Status: This is an independent, open-source utility. It is not affiliated with, endorsed by, or officially maintained by the SLMPD or the City of St. Louis.

🚀 Quick Start

Install

pip install geocrime-stl

Fetch/Clean/Visualize Data

import geocrime_stl as gc

data_pkg = gc.run_pipeline(4, 2026)

gc.generate_monthly_metrics(data_pkg)

gc.plot_monthly_maps(data_pkg)

🛠️ Local Setup (Alternative)

If you want to run the demo notebook locally or explore the source code, you can clone the repository directly:

git clone https://github.com/lweber89/geocrime-stl.git
cd geocrime-stl
pip install -e .

📓 Demo & Tutorial

To see a step-by-step walkthrough of the entire ETL process, check out the interactive Jupyter notebook included in this package:

👉 View the Demo Notebook

Note: If you have cloned the repository locally, you can open this file using Jupyter Lab or Jupyter Notebook to run the cells yourself.

🤝 Contributing & Pull Requests

Thank you for your interest in the project!

⚠️ Please Note: This is a personal project I developed and maintain in an effort to better understand the implementation of Python in geospatial data engineering / solutions architecture. I am not accepting pull requests or code contributions at this time.

If you find a bug or have an idea, feel free to open an Issue to let me know, or feel free to fork the repository and adapt it for your own personal needs!

📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

🔗 Project Links

GitHub Repository: https://github.com/lweber89/geocrime-stl

PyPI Home: https://pypi.org/project/geocrime-stl/