A data-driven expense tracking application designed to help users manage their finances intelligently. This project enables users to log daily expenses, set monthly budgets, and visualize spending patterns using interactive graphs and charts. Built with Python and powered by data science libraries, it offers both analytical depth and intuitive visual feedback.
- Expense Logging: Record daily transactions with categories and timestamps.
- Budget Setting: Define monthly or category-wise budgets and get alerts when limits are exceeded.
- Data Analysis: Summarize spending trends using descriptive statistics.
- Visualizations:
- Pie Charts for category-wise expense breakdown
- Bar & Line Graphs for monthly trends
- Heatmaps for identifying peak spending periods
- Smart Insights: Detect overspending, suggest savings, and highlight anomalies.
- Data Persistence: Store and retrieve data using CSV or database integration.
- User-Friendly Interface (optional): CLI or GUI for seamless interaction.
| Tool/Library | Purpose |
|---|---|
| Python | Core programming language |
| Pandas | Data manipulation and storage |
| NumPy | Numerical operations and calculations |
| Matplotlib | Static visualizations (bar, line, pie charts) |
| Seaborn | Enhanced statistical plots (heatmaps, trends) |
| Datetime | Timestamping and date-based filtering |
- Personal finance tracking
- Budget planning and monitoring
- Expense visualization for individuals or small teams
- Financial behavior analysis