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FEC Campaign Finance Integration - Implementation Summary

✅ What Was Added​

1. Pipeline Module​

File: pipeline/create_campaigns_gold_tables.py

Creates 4 campaign finance gold tables per state:

  • campaigns_candidates.parquet - Federal candidates (House, Senate, President)
  • campaigns_committees.parquet - PACs and campaign committees
  • campaigns_contributions.parquet - Individual contributions $200+
  • campaigns_nonprofit_donors.parquet - Nonprofit leadership political giving analysis

Key Features:

  • State-specific data extraction
  • Links to nonprofits via employer matching
  • Links to nonprofit officers via name matching
  • Configurable contribution limits and cycle years

2. Example Demo Script​

File: examples/demo_fec_integration.py

Interactive demonstration of FEC API capabilities:

  • Search for candidates in a state
  • Find contributions from specific employers
  • Track nonprofit leadership donations
  • Create gold tables for integration

Usage:

# Basic demo
python examples/demo_fec_integration.py --state MA

# Search specific employer
python examples/demo_fec_integration.py --state MA --employer "Community Health"

# Create gold tables
python examples/demo_fec_integration.py --state MA --create-gold-tables

3. Comprehensive Documentation​

File: website/docs/integrations/fec-campaign-finance.md

Complete integration guide including:

  • API access setup (get free key from api.data.gov)
  • Gold table schemas
  • Use case examples
  • Data model integration
  • Advanced usage patterns
  • Best practices

Complements existing file: website/docs/integrations/fec-political-contributions.md

🔄 Integration with Existing Data Model​

Data Linkages​

The FEC integration connects to existing gold tables:

campaigns_contributions.parquet
    ├─► contributor_employer  ───────► nonprofits_organizations.organization_name
    └─► contributor_name      ───────► contacts_nonprofit_officers.officer_name

campaigns_nonprofit_donors.parquet (Analysis Table)
    ├─► ein                   ───────► nonprofits_organizations.ein
    ├─► organization_name     ───────► nonprofits_organizations.organization_name
    └─► contributor_name      ───────► contacts_nonprofit_officers.officer_name

campaigns_candidates.parquet
    └─► state                 ───────► State-partitioned data structure

campaigns_committees.parquet
    └─► state                 ───────► State-partitioned data structure

Use Cases Enabled​

  1. Track Political Influence on Grant Awards

    # Load data
    contributions = pd.read_parquet('data/gold/states/MA/campaigns_contributions.parquet')
    grants = pd.read_parquet('data/gold/states/MA/grants_revenue_sources.parquet')

    # Analyze correlation between political giving and grant receipt

  2. Identify Politically Active Nonprofit Leaders

    # Load nonprofit donor analysis
    donors = pd.read_parquet('data/gold/states/MA/campaigns_nonprofit_donors.parquet')

    # See which nonprofit officers donate politically
    print(donors.groupby('organization_name')['contribution_amount'].sum())

  3. Map Donor Networks in Healthcare Policy

    # Find health sector political contributions
    health_contribs = contributions[
        contributions['contributor_employer'].str.contains('Health', case=False, na=False)
    ]

📊 Directory Structure​

data/gold/states/{STATE}/
├── campaigns_candidates.parquet          ← NEW
├── campaigns_committees.parquet          ← NEW  
├── campaigns_contributions.parquet       ← NEW
├── campaigns_nonprofit_donors.parquet    ← NEW (Analysis)
├── nonprofits_organizations.parquet      (Links via employer)
├── contacts_nonprofit_officers.parquet   (Links via name)
└── grants_revenue_sources.parquet        (Cross-reference)

🚀 Quick Start​

1. Get FEC API Key​

Visit: https://api.data.gov/signup/

  • Free tier: 1,000 requests/hour
  • Instant activation

2. Set Environment Variable​

echo 'FEC_API_KEY="your_key_here"' >> .env

3. Create Gold Tables​

# Activate environment
source .venv/bin/activate

# Create campaign finance tables for Massachusetts
python pipeline/create_campaigns_gold_tables.py \
  --state MA \
  --cycle 2024 \
  --max-contributions 10000

4. Analyze Data​

import pandas as pd

# Load nonprofit donor analysis
donors = pd.read_parquet('data/gold/states/MA/campaigns_nonprofit_donors.parquet')

# Top nonprofit organizations by political giving
print(donors.groupby('organization_name').agg({
    'contribution_amount': 'sum',
    'contributor_name': 'count'
}).sort_values('contribution_amount', ascending=False).head(10))

📖 API Reference​

Main Classes​

CampaignsGoldTableCreator - Pipeline for creating gold tables

  • create_campaigns_candidates(cycle) - Extract candidate data
  • create_campaigns_committees(cycle) - Extract committee data
  • create_campaigns_contributions(min_amount, max_records, cycle) - Extract contributions
  • create_campaigns_nonprofit_donors(contributions_df) - Analyze nonprofit leadership donations
  • create_all_campaigns_tables(cycle, min_contribution_amount, max_contributions) - Run full pipeline

OpenFECAPI (from discovery/fec_integration.py) - API client

  • search_individual_contributions(...) - Search contributions
  • search_candidates(...) - Find candidates
  • search_committees(...) - Find PACs/committees

🔗 Related Files​

Existing Files (Enhanced)​

New Files (Created)​

🎯 Future Enhancements​

Potential additions to consider:

  1. Add to main orchestration script

    • Update scripts/create_all_gold_tables.py to include campaigns pipeline

  2. Dashboard integration

    • Add FEC visualizations to React app
    • Display political connections on nonprofit profiles
    • Show donor network graphs

  3. Automated analysis

    • Scheduled updates (campaigns data updated daily by FEC)
    • Alerts for new major contributions
    • Influence score calculations

  4. Extended matching

    • Fuzzy name matching for officers
    • Organization name normalization
    • Cross-reference with local officials data

📝 Documentation Links​

✅ Checklist for Integration​

  • Create pipeline module for gold table generation
  • Add example demo script
  • Write comprehensive documentation
  • Add to main orchestration script (optional)
  • Create React dashboard components (optional)
  • Set up automated updates (optional)

Implementation Date: April 28, 2026 Author: GitHub Copilot License: MIT (consistent with project)