mapdata_fips_aggregation

Main Features & Purpose

This repository is a geospatial data processing pipeline that combines multiple data sources and geocoding methods to enrich address data with FIPS (Federal Information Processing Standards) codes for mapping and choropleth visualization.

Core Components

1. Selenium-Based FIPS Code Scraping (selenium_fips/)

• Web scraping automation using Selenium WebDriver with Chrome/Brave browser
• Targets the US Census Bureau's geocoding service (https://geocoding.geo.census.gov/geocoder/geographies/coordinates?form)
• Coordinate-to-FIPS conversion: Takes latitude/longitude coordinates and retrieves corresponding FIPS codes
• State-specific processing: Separate notebooks for each state (NY example shown)
• Error handling: Manages timeouts, missing data, and multiple FIPS returns
• Data cleaning: Removes brackets, handles empty results, processes regex patterns

2. Google Geocoding API Integration (google_geocoder/)

• Address geocoding using Google Maps Geocoding API
• Converts physical addresses to latitude/longitude coordinates
• Batch processing with progress tracking (tqdm)
• Error handling for addresses not found
• API key management for Google services

3. Census Geocoder Alternative (census_geocoder/)

• Backup geocoding solution using the US Census Bureau's public geocoding API
• Direct address-to-coordinates-to-FIPS pipeline that bypasses Google's service entirely
• Rate-limited but free alternative: Slower processing speed but no API costs or quotas
• Fallback mechanism: Used when Google API limits are reached or exceeded
• State-specific implementations: 14 separate notebooks for different states
• Integrated workflow: Combines geocoding and FIPS retrieval in a single API call
• Dependencies: Uses selenium, BeautifulSoup, requests, and pandas for processing
• Cost-effective scaling: Allows continued processing when commercial API budgets are exhausted

4. Data Pipeline Architecture

The workflow follows multiple pathways:

Primary Path: Raw Address Data → Google Geocoding → Lat/Long Coordinates → Census FIPS Scraping → Enriched Dataset

Alternative Path: Raw Address Data → Census Geocoder → Lat/Long + FIPS → Enriched Dataset

Key Technical Features

Multi-Source Data Integration

• Combines Google's geocoding accuracy with Census Bureau's authoritative FIPS data
• Fallback mechanisms: Uses existing FIPS data when available, fills gaps with scraped data
• Hybrid approach: Primary Google API with Census Bureau backup for cost management

State-by-State Processing

• Modular approach with separate processing for each US state
• Scalable architecture for handling large datasets across multiple states
• State-specific FIPS code validation (e.g., NY codes starting with "36")

Robust Error Handling

• Manages web scraping timeouts and connection issues
• Handles missing geocoding results
• Data quality checks: Validates coordinate ranges and FIPS code formats

Data Merging & Enrichment

• Pandas-based data manipulation for joining datasets
• Preserves original data while adding new FIPS information
• Column management: Handles duplicate columns and data type conversions

Use Cases & Applications

Choropleth Mapping

• Enables creation of color-coded maps based on geographic regions
• FIPS codes provide standardized geographic boundaries for visualization

Geographic Data Analysis

• Supports analysis of loan data, demographic information, or other location-based datasets
• Enables aggregation by census tracts, counties, or other geographic units

Data Standardization

• Converts inconsistent address formats into standardized geographic identifiers
• Creates linkages between different geographic datasets

Technical Stack

• Python Libraries: pandas, selenium, requests, BeautifulSoup, tqdm
• Web Technologies: Chrome WebDriver, Google Maps API
• Data Sources: US Census Bureau, Google Geocoding Service
• Output Format: CSV files with enriched geographic data

Repository Structure Benefits

• Modular design allows for easy state-by-state processing
• Jupyter notebooks provide interactive development and debugging
• Separation of concerns between geocoding and FIPS retrieval
• Reusable components across different geographic regions
• Cost-effective redundancy: Multiple geocoding pathways ensure continuous processing regardless of API limitations

This repository essentially serves as a comprehensive geocoding and geographic enrichment pipeline that transforms raw address data into map-ready datasets with standardized FIPS codes, making it valuable for any application requiring US geographic data visualization or analysis.