🗺️ PyMapGIS Documentation

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

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🚀 Quick Start

pip install pymapgis

import pymapgis as pmg

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

# Calculate housing cost burden
data["cost_burden_rate"] = data["B25070_010E"] / data["B25070_001E"]

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

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📚 Documentation

🚀 Quick Start

Get up and running in 5 minutes. Create your first interactive map with real Census data.

📖 User Guide

Comprehensive guide covering all PyMapGIS concepts, features, and workflows.

🔧 API Reference

Complete API documentation with function signatures, parameters, and examples.

💡 Examples

Real-world examples and use cases with complete, runnable code.

🧑‍💻 Developer Docs

Information for contributors: architecture, setup, and extending PyMapGIS.

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✨ 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

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📊 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

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🎯 Example Use Cases

Housing Analysis

# Housing cost burden analysis
housing = pmg.read("census://acs/acs5?year=2022&geography=county&variables=B25070_010E,B25070_001E")
housing["cost_burden_rate"] = housing["B25070_010E"] / housing["B25070_001E"]
housing.plot.choropleth(column="cost_burden_rate", title="Housing Cost Burden").show()

Labor Market Analysis

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

Demographic Mapping

# Population density
pop = pmg.read("census://acs/acs5?year=2022&geography=county&variables=B01003_001E")
pop["density"] = pop["B01003_001E"] / (pop.geometry.area / 2589988.11)  # per sq mile
pop.plot.choropleth(column="density", title="Population Density").show()

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🛠️ Installation

From PyPI (Recommended)

pip install pymapgis

From Source

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

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🤝 Community

• GitHub Repository - Source code and development
• PyPI Package - Package installation
• Issues - Bug reports and feature requests
• Discussions - Community Q&A
• Contributing Guide - How to contribute
• Developer Documentation - For contributors and those extending PyMapGIS.

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📄 License

PyMapGIS is open source software licensed under the MIT License.

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Made with ❤️ by the PyMapGIS community