University Data Analysis

A Flask-based web application to analyze and visualize university data.
Built with Python, Pandas, Matplotlib, and Flask, this project provides both a web interface and REST APIs to perform data exploration, generate insights, and visualize results.

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Features

• Data Analysis: Summarizes university data (counts, averages, distributions, etc.)
• Visualization: Generates plots/graphs with Matplotlib for trends and comparisons
• REST APIs: Exposes processed data and visualizations via endpoints
• CSV Handling: Reads and processes CSV datasets
• Web UI: Simple interface to view results (Flask + HTML templates)

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Tech Stack

• Backend: Flask (Python)
• Data Processing: Pandas, NumPy
• Visualization: Matplotlib
• Frontend: HTML, CSS, Bootstrap (via Flask templates)

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Project Structure

University-Data-Analysis/
├── app.py # Main Flask application
├── analysis.py # Data analysis & visualization
├── data_loader.py # Data loading/cleaning utilities
├── csv/ # Raw data files
├── static/ # Static files (CSS, charts)
├── templates/ # HTML templates
├── requirements.txt # Dependencies
└── README.md # Documentation

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Installation & Setup

1. Clone the repository

   git clone https://github.com/deeppatel1809/University-Data-Analysis.git
   cd University-Data-Analysis

2. Create a virtual environment (recommended)

   python -m venv venv

3. Activate the virtual environment

   Windows:

    venv\Scripts\activate
   

   Linux / macOS:

    source venv/bin/activate
   

4. Install dependencies

   pip install -r requirements.txt

5. Run the Flask application

   flask run

6. Open in browser:

   http://127.0.0.1:5000/