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📈 Finance Tracker Dashboard

An interactive personal finance dashboard built with Streamlit and Python. This tool helps users automatically analyze and visualize their spending habits by processing and categorizing uploaded bank statements (CSV or Excel).

🚀 Key Features

  • Automated Data Processing: Upload messy bank statements (CSV or Excel) and watch the app automatically clean the data and categorize transactions (e.g., Food, Travel, Rent, Income/Transfer).
  • Interactive Filtering: Dynamically filter your data using sidebar controls for:
    • Specific Date Ranges
    • Transaction Categories
    • Text Search (e.g., search for "Target" or "Uber")
  • Comprehensive Summary Metrics (KPIs): Get immediate insights into your Total Expenses, Total Income/Deposits, Transaction Count, and Average Transaction Value.
  • Visual Reports:
    • Spending by Category (Bar Chart): See where most of your money is going.
    • Category Distribution (Pie Chart): Understand the percentage breakdown of your expenses.
    • Expense Timeline: A line chart showing your expense volume over time with an overlaid scatter plot highlighting individual transaction densities.
  • Detailed Ledger: Analyze the clean, formatted transaction data in a sortable, full-width table.

🛠️ How to Run Locally

Prerequisites

  • Python 3.7 or higher installed on your system.

Automated Setup

To quickly set up the virtual environment and install dependencies, simply use the provided setup scripts:

For Windows:

setup.bat

For macOS / Linux:

./setup.sh
# or
bash setup.sh

Manual Setup

If you prefer setting it up manually, run the following commands in your terminal:

  1. Create a virtual environment:

    python -m venv venv
  2. Activate the virtual environment:

    • Windows:
      venv\Scripts\activate
    • macOS/Linux:
      source venv/bin/activate
  3. Install the required dependencies:

    pip install -r requirements.txt

Running the App

Once your setup is complete and the virtual environment is activated, run the Streamlit dashboard using:

streamlit run app.py

The app will automatically open in your default web browser at http://localhost:8501.


💡 Tip: Upload your personal statement using the sidebar to start tracking immediately!

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An interactive Streamlit dashboard for automatically cleaning, categorizing, and visualizing personal finance statements.

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