📊 Student Performance Analysis

A data analysis project exploring how various student habits (e.g., study hours, screen time, exercise, part-time jobs, and extracurricular activities) correlate with academic performance.

🔍 Key Questions Explored

• Do students who exercise at least 3 times per week perform better?
• How does parental education level influence student habits?
• Do part-time jobs or extracurricular activities reduce study effectiveness?
• What habits most strongly correlate with academic success?

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🧰 Technologies Used

• Python 3.10+
• Pandas – data analysis and transformation
• Matplotlib – visualizations and grouped bar plots
• SQLAlchemy – SQL interface via Python
• PostgreSQL – SQL database for structured queries
• Jupyter Notebook – data exploration and reporting

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📁 Project Structure

student-performance-analysis/
│
├── data/               # Raw and processed CSVs
├── notebooks/          # Jupyter notebooks for each analysis question
├── sql/                # SQL queries used for filtering & aggregation
├── venv/               # Virtual environment (excluded from Git)
│
├── .gitignore          # Git ignore rules for venv, pycache, etc.
├── .gitattributes      # Git attributes (e.g., line endings)
├── README.md           # Project documentation
└── requirements.txt    # Python dependencies