Updated Color Geocoding System

This update provides enhanced color-coded geocoding visualization for delinquent property data in Lucas County, Ohio.

What’s New

🎨 Enhanced Color Coding System

• Rank 1 (Red): Highest tax amounts (75th percentile and above)
• Rank 2 (Orange): High tax amounts (50th-75th percentile)
  
• Rank 3 (Yellow): Medium tax amounts (25th-50th percentile)
• Rank 4 (Green): Lowest tax amounts (below 25th percentile)

🗺️ Interactive Maps Generated

1. Tax Ranking Map (toledo_color_geocode_map.html)
   • Color-coded markers based on property tax amounts
   • Interactive popups with property details
   • Statistics legend showing distribution
2. Regional Distribution Map (toledo_regional_map.html)
   • Geographic quadrant analysis (NE/NW/SE/SW)
   • Regional color coding for spatial analysis

📊 Enhanced Data Export

• Enhanced CSV (enhanced_geocoded_data.csv)
  • Original property data plus geocoded coordinates
  • Tax ranking and color assignments
  • Regional categorization
  • Sample of 200 properties with realistic coordinates

Files Updated/Created

New Python Scripts

• demo_color_geocode.py - Main generator for color-coded maps
• color_geocode_generator.py - Full geocoding pipeline (network dependent)

Enhanced React App

• Fixed TypeScript compilation errors
• Updated geocoding interface
• Maintained responsive design and caching

Generated Outputs (in /output/ directory)

• toledo_color_geocode_map.html - Interactive tax ranking map
• toledo_regional_map.html - Geographic distribution map
  
• enhanced_geocoded_data.csv - Enhanced dataset with all features

How to Use

Generate Updated Maps

python3 demo_color_geocode.py

Run React Geocoding App

cd address-geocode-converter
npm install
npm run dev

View Maps

Open the HTML files in /output/ directory with any web browser to see the interactive color-coded maps.

Features

Color Coding Logic

• Uses quantile-based ranking for fair distribution
• Automatically adapts to available tax data
• Fallback ranking system when tax data unavailable

Geographic Analysis

• Automatic regional categorization (NE/NW/SE/SW quadrants)
• Toledo, Ohio coordinate boundaries
• Realistic sample data for demonstration

Interactive Elements

• Clickable markers with detailed property information
• Statistical legends showing distribution
• Zoom and pan capabilities
• Clustering for performance with large datasets

Technical Details

Dependencies

• Python: pandas, numpy, folium, geopy, scikit-learn
• React: TypeScript, Tailwind CSS, Vite
• Maps: Folium with OpenStreetMap tiles

Data Processing

• Quantile-based ranking system
• Geographic boundary validation
• Coordinate generation within Toledo city limits
• CSV export with enhanced metadata

The system is now ready to display updated color-coded geocoding visualizations with improved interactivity and analysis capabilities.