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🎓 Student Performance Analysis

Project Objective

Analyze student academic data to understand:

  • Average marks per subject

  • Top and bottom performing students

  • Relationship between attendance and academic performance

  • Subject-wise performance distribution

This demonstrates EDA, correlation analysis, and data visualization, which are core data analyst skills.

Overview

This project analyzes student academic performance using Python data analytics techniques.

Tools Used

  • Python
  • Pandas
  • Seaborn
  • Matplotlib

Key Analysis

  • Subject-wise average scores
  • Top and bottom performing students
  • Attendance vs performance
  • Correlation analysis

Insights

Higher attendance is positively correlated with better academic performance.

Author

notyoursreejon

About

A data analytics project analyzing student academic performance using Python. Includes EDA, subject-wise averages, attendance vs performance analysis, and correlation insights using Pandas, Seaborn, and Matplotlib.

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