📊 Bank Transaction Visualizer

A Python web application that turns raw text alerts from your bank into an interactive financial dashboard.

📖 About The Project

Managing finances by reading through hundreds of unstructured SMS or email alerts is tedious and difficult. This tool automates that process. You simply upload a text file containing your raw transaction alerts, and the application parses, cleans, and visualizes your spending habits instantly.

✨ Key Features

• Automated Parsing: Uses advanced pattern matching (Regex) to extract dates, amounts, and vendor names from messy text.
• Smart Categorization: Automatically organizes transactions into clear categories like 'Food & Coffee', 'Groceries', and 'Transport'.
• Indian Currency Formatting: Features a custom formatter to display numbers in the Indian system (Lakhs and Crores) for better readability.
• Interactive Dashboard: view key metrics (Total Spent, Net Flow), spending trends over time, and category breakdowns.

⚙️ How It Works

The application runs as a linear data pipeline:

1. Upload: You drag and drop your transactions.txt file into the web interface.
2. Read & Parse: The script reads the file line-by-line and uses Regular Expressions to extract structured data (date, amount, vendor, type) from the raw text.
3. Process: The data is loaded into Pandas, where it is cleaned, and vendors are mapped to specific spending categories.
4. Visualize: Streamlit uses the processed data to render interactive charts and summary metrics on your screen.

🛠️ Technologies Used

• Python 3: The core programming language.
• Streamlit: Used to build the user interface and interactive dashboard.
• Pandas: Handles all data structuring, cleaning, and aggregation.
• re (Regular Expressions): The built-in Python module used as the parsing engine to "read" the text alerts.

🚀 Quick Start

Prerequisites

• Python 3.x installed on your system.

Installation & Run

1. Clone this repository:

   git clone [https://github.com/harshkad/bank-transaction-visualizer.git](https://github.com/harshkad/bank-transaction-visualizer.git)

2. Install the required packages:

   pip install streamlit pandas

3. Run the application:

   streamlit run dashboard.py

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