DC South East Study

Anacostia DC Air pollution and water warning system using EJScreen data.

Overview

This project analyzes environmental justice data for the District of Columbia, with a focus on the Anacostia area. It integrates EJScreen API data with TIGER/Line shapefiles to create spatial visualizations and analyses of environmental and demographic indicators.

Features

• Data Filtering: Filter EJScreen data for DC (District of Columbia)
• API Integration: Fetch environmental and demographic data from the EJScreen API
• Spatial Analysis: Merge data with TIGER/Line shapefiles for geographic visualization
• Batch Processing: Fetch data for multiple block groups with rate limiting

Project Structure

dc-south-east-study/
├── data/
│   ├── raw/              # Raw data files and shapefiles
│   └── processed/        # Processed data and merged shapefiles
├── notebooks/            # Jupyter notebooks for analysis
├── src/                  # Source code
│   ├── config.py         # Configuration constants
│   ├── start.py          # Filter EJScreen data for DC
│   ├── get_data_from_api.py  # Single API data fetch
│   ├── get_study_data.py      # Batch API data fetching
│   └── clean_data.py     # Merge data with shapefiles
├── pyproject.toml        # Poetry dependencies
└── requirements.txt      # pip dependencies

Getting Started

Prerequisites

• Python 3.10 or higher
• Poetry (recommended) or pip

Installing Poetry

macOS (using Homebrew):

brew install pipx
pipx ensurepath
pipx install poetry

Windows (using Scoop):

scoop install pipx
pipx ensurepath
pipx install poetry

Alternative (using pip):

pip install poetry

Installing Dependencies

Using Poetry (recommended):

poetry install

Using pip:

pip install -r requirements.txt

Usage

Filter EJScreen Data for DC

Filter the national EJScreen dataset to only include DC data:

poetry run python src/start.py
# or
python src/start.py

This will:

• Read the EJScreen tract-level data
• Filter for DC (ST_ABBREV == 'DC')
• Save filtered data to data/processed/track/

Fetch Data from EJScreen API

Single Block Group:

poetry run python src/get_data_from_api.py

Multiple Block Groups (Anacostia area):

poetry run python src/get_study_data.py

This will:

• Fetch data for all block groups in southeast Anacostia
• Fetch city-level data for Washington, DC
• Save results to CSV files in data/processed/block_group/

Merge Data with Shapefiles

Merge filtered CSV data with TIGER/Line shapefiles for spatial analysis:

poetry run python src/clean_data.py

This will:

• Load TIGER/Line tract shapefiles
• Merge with filtered EJScreen data
• Save merged shapefile to data/processed/shapefiles/track/

Configuration

Configuration constants are defined in src/config.py, including:

• File paths
• API endpoints
• Block group IDs
• Request delays

Development

Code Quality

The project uses modern Python practices:

• Type hints
• Pathlib for file paths
• Error handling
• Configuration management

Development Tools

Development dependencies (installed with Poetry):

• black: Code formatting
• ruff: Fast linting
• mypy: Type checking
• pytest: Testing

Run formatting:

poetry run black src/

Run linting:

poetry run ruff check src/

Data Sources

• EJScreen: EPA's Environmental Justice Screening and Mapping Tool
• TIGER/Line: U.S. Census Bureau geographic boundary files

License

See LICENSE file for details.

Contributing

1. Ensure code follows the project's style guidelines
2. Add type hints to all functions
3. Include docstrings for public functions
4. Test your changes before submitting