OSM Address Cleaner

A Python tool to download and clean OpenStreetMap (OSM) building data with address normalization capabilities.

Features

• Download OSM building data by:
  • Place name (e.g., "Manhattan, New York")
  • Bounding box coordinates (north, south, east, west)
• Comprehensive address cleaning:
  • Street name normalization
    • Expands common abbreviations (St → Street, Rd → Road, etc.)
    • Handles directional prefixes/suffixes (N, S, E, W, NE, NW, SE, SW)
    • Special handling for Mc/Mac names (e.g., "Mc Donald" → "McDonald")
    • Proper handling of ordinal numbers (1st, 2nd, 3rd)
    • Smart title casing with preserved articles
  • City name cleaning
    • Expands common abbreviations (St. → Saint, Ft. → Fort, Mt. → Mount)
    • Proper capitalization for complex names
  • US ZIP code validation
• Generates cleaning reports with statistics

Installation

1. Clone this repository:

git clone https://github.com/yourusername/osm_address_cleaner.git
cd osm_address_cleaner

2. Install required dependencies:

pip install -r requirements.txt

Usage

Basic Usage

Run the script with default settings (downloads Manhattan buildings as an example):

python cleaner.py

Python API

from cleaner import download_osm_buildings, clean_osm_addresses

# Download buildings by place name
download_osm_buildings(
    place_name="Chicago, Illinois",
    save_path="data/raw_osm_buildings.geojson"
)

# Or download by bounding box (north, south, east, west)
download_osm_buildings(
    bbox=(42.0, 41.8, -87.5, -87.8),
    save_path="data/raw_osm_buildings.geojson"
)

# Clean the addresses
clean_osm_addresses(
    input_path="data/raw_osm_buildings.geojson",
    output_path="data/cleaned/cleaned_osm_buildings.gpkg",
    report_path="reports/cleaning_report.csv"
)

Address Cleaning Examples

The tool performs comprehensive cleaning of address components:

# Street Names
"MC DONALD   RD" → "McDonald Road"
"N.  MAIN ST." → "North Main Street"
"123RD   AVE" → "123rd Avenue"

# City Names
"st. LOUIS" → "Saint Louis"
"FT. WORTH" → "Fort Worth"
"MT VERNON" → "Mount Vernon"

Project Structure

osm_address_cleaner/
├── cleaner.py          # Main script
├── requirements.txt    # Python dependencies
├── data/              # Data directory
│   └── cleaned/       # Cleaned output files
└── reports/           # Cleaning reports

Dependencies

• osmnx: OpenStreetMap data download
• geopandas: Geospatial data handling
• pandas: Data processing
• shapely: Geometric operations

License

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