Student Academic Performance Analysis

This Jupyter Notebook explores a dataset on student academic performance. It covers data cleaning, feature engineering, visualization, and analysis to uncover key factors influencing student success in exams.

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What You'll Learn

• Why analyzing student performance matters
• How to load and inspect real-world education data
• Handling and visualizing missing values
• Creating new features (e.g., grading systems)
• Data visualization using Seaborn and Matplotlib

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📂 Table of Contents

1. Introduction
2. Loading Libraries and Data
3. Quick Look at the Data
4. Visualizing Missing Values
5. Data Preparation
6. Data Visualization

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