Student-Performance-Analysis-and-Visualization

A Python-based data analytics project that analyzes student academic performance using Pandas and Matplotlib through statistical calculations and multiple visualization techniques.

Student Performance Analysis and Visualization

Project Overview

(Short description of the project)

Objectives

• Analyze student performance
• Generate rankings and grades
• Create visualizations

Questions Solved

1. How can student academic data be imported and organized?
2. How can total and average marks be calculated?
3. How can grades be assigned automatically?
4. How can topper and rankings be identified?
5. How can top-performing students be compared using bar charts?
6. How can subject-wise performance trends be analyzed?
7. How can overall grade distribution be visualized?
8. How can relationships between subjects be analyzed using scatter plots?
9. How can marks distribution be analyzed using histograms?
10. How can subject averages be compared?
11. How can subject trends be visualized using area charts?
12. How can correlation between subjects be identified?
13. How can overall class performance be summarized?

Technologies Used

• Python
• Pandas
• NumPy
• Matplotlib

Visualizations Generated

• Bar Chart
• Line Chart
• Pie Chart
• Scatter Plot
• Histogram
• Horizontal Bar Chart
• Area Chart

How to Run

Prerequisites:

• Python 3.x
• Pandas
• NumPy
• Matplotlib

Steps:

1. Download or clone the repository.
2. Install dependencies using requirements.txt.
3. Run the Python script.
4. Explore the generated visualizations and analysis results.

The project uses a CSV dataset containing student records with marks in:

• Mathematics
• Science
• English

The dataset is included as students.csv

Sample Visualizations

Top 7 Student Performance

Grade Distribution

Math vs Science Performance

Marks Distribution

Author

Atul Tyagi

LinkedIn: http://www.linkedin.com/in/imatultyagi

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