Interactive dashboard for analyzing stock dividend portfolios and projecting future growth. Built with Streamlit, Pandas, and Plotly, this application demonstrates modern data visualization techniques and financial modeling in Python.
This project serves as a comprehensive tool for dividend investors to track their portfolio performance and forecast future returns. It was designed to showcase proficiency in:
- Full-stack Python Development: From data processing to frontend visualization.
- Data Engineering: Cleaning, transforming, and aggregating raw financial data.
- UI/UX Design: Creating a responsive, dark-mode optimized interface with custom CSS.
- Financial Modeling: Implementing DRIP (Dividend Reinvestment Plan) calculators and growth projections.
- Interactive Metrics: Real-time KPI tiles with gradient styling for quick portfolio health checks.
- Dynamic Charts: Plotly-powered bar charts and Nivo pie charts for asset allocation analysis.
- Responsive Design: Optimized layout that adapts to various screen sizes.
- DRIP Calculator: Simulate the compound effect of reinvesting dividends over time.
- Growth Projections: Customizable parameters (years, growth rate) to model future income scenarios.
- Automated Ingestion: Seamlessly handles CSV data imports.
- Data Validation: Ensures data integrity with type checking and error handling.
- Smart Aggregation: Dynamic grouping of tickers and sectors.
- Core:
Python 3.12 - Web Framework:
Streamlit - Data Manipulation:
Pandas - Visualization:
Plotly Express,Streamlit Elements - Dependency Management:
Poetry