Military & Firearm Analysis Toolkit

📊 Overview

This comprehensive Python-based toolkit provides data-driven insights into the relationships between military populations, firearm ownership, mental health outcomes, and economic impacts across U.S. states and counties.

✨ Key Features

Data Collection

• Automatic caching - Reduces API calls and speeds up repeated analyses
• Graceful fallbacks - Works with or without API keys using sample data
• Robust error handling - Handles network issues and missing data
• Metadata tracking - JSON metadata for every dataset with timestamps

Analysis Capabilities

• State-level analysis - All 50 states plus DC and territories
• County-level support - Census API provides county granularity
• Correlation analysis - Statistical relationships between variables
• Risk ratio calculations - Veteran vs civilian outcome comparisons

Visualizations

• Publication-ready - 300 DPI output suitable for reports
• Accessible color schemes - Colorblind-friendly palettes
• Comprehensive labeling - Clear titles, axes, and legends
• Statistical overlays - Trend lines and reference markers

🚀 Quick Start

1. Create a virtual environment

   python3 -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

2. Install dependencies

   pip install -r requirements.txt

3. Configure API access (optional)

   cp .env.example .env
   # Edit .env and add your Census API key

   Get your free key at: https://api.census.gov/data/key_signup.html

4. Run the analysis

   python military_firearm_analysis.py

📚 Data Sources

All data comes from authoritative government and academic sources:

📁 Output Files

Data Directory (data/)

• military_firearm_veterans.csv - Veteran population by state
• military_firearm_active_duty.csv - Active duty personnel distribution
• military_firearm_firearms.csv - Firearm ownership rates
• military_firearm_ffl.csv - Federal Firearm Licensee counts
• military_firearm_suicide.csv - Veteran suicide rates and risk ratios
• military_firearm_ptsd.csv - PTSD prevalence estimates
• military_firearm_spouse_employment.csv - Military spouse employment data
• military_firearm_va_healthcare.csv - VA healthcare utilization
• military_firearm_economic_impact.csv - Military base economic impacts
• military_firearm_merged_analysis.csv - Complete merged dataset

Output Directory (output/)

• military_firearm_comprehensive_dashboard.png - 9-panel overview (300 DPI)
• military_firearm_correlations.png - 6-panel correlation scatter plots (300 DPI)
• military_base_economic_impact.png - Economic analysis visualization (300 DPI)

📈 Generated Visualizations

The toolkit generates publication-ready visualizations (300 DPI) combining data from multiple authoritative sources.

Comprehensive Dashboard (State-Level Analysis)

9-panel overview: veteran populations, active duty, firearm ownership, veteran suicide risk ratios, FFL density, VA healthcare utilization, and correlation heatmap.

Correlation Analysis

6 scatter plots examining key relationships: veteran population vs firearm ownership, firearm ownership vs veteran suicide rates, FFL density vs ownership, PTSD prevalence vs VA utilization, veteran population vs suicide risk, and active duty density vs military spouse unemployment.

Military Base Economic Impact

Major military installation economic contributions: personnel vs civilian job creation, and state-level economic impact distribution.

Veterans Distribution (County-Level Map)

County-level choropleth: Veterans per 100 residents. Shows geographic concentration of veteran populations with highest densities near military installations.

Active Duty Distribution (County-Level Map)

County-level choropleth: Active duty / Armed Forces population per 10,000 residents. Highlights counties with major military bases and installations.

State Military Population (Stacked Bar)

Active duty + Veterans by state (stacked). States sorted by total military presence, showing combined active duty and veteran populations.

💡 Usage Examples

Basic Analysis

from military_firearm_analysis import main

# Run complete analysis
all_data, merged_data = main()

Load Previously Saved Data

import pandas as pd

# Load merged dataset
merged = pd.read_csv('data/military_firearm_merged_analysis.csv')

# Perform custom analysis
print(merged.describe())
print(merged.corr())

Custom Visualization

from military_firearm_analysis import (
    get_veteran_data_by_state,
    get_firearm_ownership_by_state
)
import matplotlib.pyplot as plt

veterans = get_veteran_data_by_state()
firearms = get_firearm_ownership_by_state()

# Create custom plot
# ... your code here

🔬 Adjacent Research Topics

The toolkit identifies 10 categories of related research areas with specific data sources:

⚠️ Disclaimer