Congressional Committee Analysis
I built a real-time dashboard that tracks congressional committee activity and bill processing workflows. The project uses the Congress.gov API to fetch committee data and displays it through interactive charts showing the most active committees, bill counts per committee, and committee type distributions.
I started with a basic bill tracker but realized committee analysis was more interesting and valuable. The dashboard shows which committees are processing the most bills, how House vs Senate committees compare, and the breakdown between Standing, Select, and Joint committees. I added an auto-refresh toggle so users can see live updates when they want to.
Key Features:
- Committee activity rankings and bill counts
- House vs Senate committee comparisons
- Committee type analysis (Standing, Select, Joint)
- Interactive charts with Chart.js
- Optional auto-refresh functionality
- Real congressional data from Congress.gov API
Technical Skills Demonstrated:
- Python API integration and data processing
- JavaScript frontend development
- Data visualization with Chart.js
- Congress.gov API v3 usage
- Automated data collection and scheduling
- Responsive web design
Voting Analysis: Georgia & Texas
This project explores partisan shifts and voter turnout in Georgia and Texas over recent election cycles. Using publicly available voting data, I cleaned and organized the information in Excel, wrote a Python script to calculate vote percentages, and visualized the results using multiple comparative charts and analyses.
Georgia and Texas were chosen due to their contrasting electoral trends: Georgia's recent swing toward Democratic candidates and Texas's evolving but traditionally Republican base. By analyzing this data over time, the project sheds light on broader regional political dynamics and highlights the importance of voter engagement and demographic shifts.
Key Findings:
- Georgia 2020 Result: Biden won with 49.5% vs Trump's 49.3% (0.2% margin)
- Texas 2020 Result: Trump won with 52.1% vs Biden's 46.9% (5.2% margin)
- Most Competitive County: Williamson County, TX (49.8% Biden vs 48.5% Trump)
- County Analysis: 89 Georgia counties vs 45 Texas counties
Technical Skills Demonstrated:
- Data Cleaning: Excel and Python for data standardization and validation
- Statistical Analysis: Vote percentage calculations and correlation analysis
- Data Visualization: Multiple chart types using matplotlib and seaborn
- Web Development: HTML/CSS for project presentation
- Geographic Analysis: County-level electoral mapping and comparison
Debate Analyzer & Argument Helper
This interactive tool helps users both analyze debates for logical fallacies and build stronger arguments based on logic principles. The Argument Helper guides you in constructing valid and sound arguments, while the Debate Analyzer highlights possible logical fallacies and rhetorical devices in any debate transcript.
Key Features:
- Build arguments with dynamic premises and soundness checks
- Educational popups for logic concepts (validity, soundness, fallacy)
- Analyze debate text for common logical fallacies
- Send statements from the analyzer to the argument builder for refinement
- Modern, user-friendly interface