pymapgis 0.1.0

Modern GIS toolkit for Python - Simplifying geospatial workflows with built-in data sources, intelligent caching, and fluent APIs

PyMapGIS

Modern GIS toolkit for Python - Simplifying geospatial workflows with built-in data sources, intelligent caching, and fluent APIs.

🚀 Quick Start

pip install pymapgis

import pymapgis as pmg

# Load Census data with automatic geometry
acs = pmg.read("census://acs/acs5?year=2022&geography=county&variables=B25070_010E,B25070_001E")

# Calculate housing cost burden (30%+ of income on housing)
acs["cost_burden_rate"] = acs["B25070_010E"] / acs["B25070_001E"]

# Create interactive map
acs.plot.choropleth(
    column="cost_burden_rate",
    title="Housing Cost Burden by County (2022)",
    cmap="Reds"
).show()

✨ Key Features

• 🔗 Built-in Data Sources: Census ACS, TIGER/Line, and more
• ⚡ Smart Caching: Automatic HTTP caching with TTL support
• 🗺️ Interactive Maps: Beautiful visualizations with Leaflet
• 🧹 Clean APIs: Fluent, pandas-like interface
• 🔧 Extensible: Plugin architecture for custom data sources

📊 Supported Data Sources

Source	URL Pattern	Description
Census ACS	census://acs/acs5?year=2022&geography=county	American Community Survey data
TIGER/Line	tiger://county?year=2022&state=06	Census geographic boundaries
Local Files	file://path/to/data.geojson	Local geospatial files

🎯 Examples

Labor Force Participation Analysis

# Traditional approach: 20+ lines of boilerplate
# PyMapGIS approach: 3 lines

acs = pmg.read("census://acs/acs5?year=2022&geography=county&variables=B23025_004E,B23025_003E")
acs["lfp_rate"] = acs["B23025_004E"] / acs["B23025_003E"]
acs.plot.choropleth(column="lfp_rate", title="Labor Force Participation").show()

Housing Cost Burden Explorer

# Load housing cost data with automatic county boundaries
housing = pmg.read("census://acs/acs5?year=2022&geography=county&variables=B25070_010E,B25070_001E")

# Calculate and visualize cost burden
housing["burden_30plus"] = housing["B25070_010E"] / housing["B25070_001E"]
housing.plot.choropleth(
    column="burden_30plus",
    title="% Households Spending 30%+ on Housing",
    cmap="OrRd",
    legend=True
).show()

🛠️ Installation

From PyPI (Recommended)

pip install pymapgis

From Source

git clone https://github.com/pymapgis/core.git
cd core
poetry install

📚 Documentation

• API Reference
• Examples Repository
• Contributing Guide

🤝 Contributing

We welcome contributions! PyMapGIS is an open-source project under the MIT license.

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

See CONTRIBUTING.md for detailed guidelines.

📄 License

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

🙏 Acknowledgments

• Built on top of GeoPandas, Leafmap, and Requests-Cache
• Inspired by the need for simpler geospatial workflows in Python
• Thanks to all contributors

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Made with ❤️ by the PyMapGIS community