Student Performance Analysis and Visualization

This project analyzes student performance data to uncover trends related to gender, ethnic groups, parental education, test preparation, and extracurricular activities. The goal is to gain insights into factors influencing academic outcomes using Exploratory Data Analysis (EDA) and visualization techniques.

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Key Insights

• Female students outnumber male students.
• Certain ethnic groups have higher participation.
• Test preparation positively impacts academic scores.
• Higher parental education correlates with better performance.
• Students engaged in extracurricular activities demonstrate varied performance patterns.

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Technologies Used

• Python
• Pandas
• NumPy
• Matplotlib
• Seaborn
• Jupyter Notebook / Google Colab

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Dataset

The dataset used in this project is available in the repository under the data/ folder:

student_data.csv

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How to Run

1. Clone the repository:

   git clone https://github.com/vigneshkavin550-netizen/Student-Perfomance-Analysis.git
   cd Student-Performance-Analysis