Analyze student academic data to understand:
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Average marks per subject
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Top and bottom performing students
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Relationship between attendance and academic performance
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Subject-wise performance distribution
This demonstrates EDA, correlation analysis, and data visualization, which are core data analyst skills.
This project analyzes student academic performance using Python data analytics techniques.
- Python
- Pandas
- Seaborn
- Matplotlib
- Subject-wise average scores
- Top and bottom performing students
- Attendance vs performance
- Correlation analysis
Higher attendance is positively correlated with better academic performance.
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