Personal Finance Tracker with Data Visualization

This project is a personal finance tracker built in Python that lets users log income and expenses, automatically categorizes transactions using simple keyword-based rules (e.g., 'Uber' → Transport), and stores everything in a local SQLite database.

Pandas is used to aggregate monthly spending by category, and Matplotlib/Plotly renders interactive charts — pie charts for category breakdown, and a line chart for balance-over-time — inside a Streamlit dashboard that updates as new transactions are added.

The app also supports importing a bank statement CSV for bulk transaction entry, and includes a simple budget-alert feature that flags categories exceeding a user-set monthly limit, giving a complete personal-finance workflow in a lightweight Python app.

Detailed Project Description

Personal Finance Tracker with Data Visualization gives the user a focused everyday tool with a clean interface, local storage of their data and optional sync or reminders.

How It Works
1. The user enters or records data (amounts, steps, notes, recordings, values).
2. The app validates and stores it locally (SQLite/Room/SharedPreferences) or in the cloud.
3. Lists, totals, charts or conversions are computed and displayed instantly.
4. Reminders/notifications run in the background where the feature applies.

Technology Roles
- Python
- Pandas
- Streamlit
- SQLite
- Plotly

Implementation Steps
1. Sketch the screens and the data each screen needs.
2. Create the project in Python, Pandas, Streamlit and set up navigation between screens.
3. Define the local data model (SQLite/Room/SharedPreferences) or cloud sync.
4. Implement the core feature (tracking, conversion, recording, reminders, playback).
5. Add background work / notifications / permissions where required.
6. Test on real devices, handle edge cases and optimise battery and performance.
7. Generate the APK and prepare screenshots and documentation.

Key Features
- Simple, fast UI
- Offline storage
- Summaries and charts
- Notifications / sync where applicable

Expected Output
On completion the student will have an installable app that keeps the user's data organised and accessible.

Deliverables
- Complete source code with comments
- Database schema / data model and screen flow
- Project report with screenshots and results
- Demonstration-ready build