📊 Student Performance Analysis

📌 Project Overview

This project is a Python-based data analysis application that analyzes student academic performance using a generated dataset. The dataset includes information such as age, gender, attendance, and subject-wise scores. The project helps in understanding student performance patterns using Python libraries.

🧠 Objectives

• Generate a realistic student performance dataset
• Analyze academic performance across multiple subjects
• Practice data filtering and processing
• Improve Python data analysis skills

🛠️ Technologies Used

• Python
• Pandas
• NumPy
• CSV File Handling

📂 Project Structure

Student_Performance_Analysis/
│
├── recordmaker.py
├── final.py
├── student_performance_6000.csv
├── filtered_output.csv
└── README.html
        

📄 Dataset Description

The dataset contains 6000 student records with the following fields:

• Student ID
• Name
• Gender
• Age
• Attendance (%)
• Math
• Science
• English
• History
• Computer

⚙️ How the Project Works

1️⃣ Dataset Generation

recordmaker.py generates random student data and saves it into a CSV file.

2️⃣ Data Analysis

final.py loads the dataset, performs filtering and analysis, and exports the results into a new CSV file.

▶️ How to Run the Project

Step 1: Clone the Repository

git clone https://github.com/jadwinder/Student_Performance_Analysis.git
        

Step 2: Navigate to Project Folder

cd Student_Performance_Analysis
        

Step 3: Install Required Libraries

pip install pandas numpy
        

Step 4: Generate Dataset

python recordmaker.py
        

Step 5: Run Analysis

python final.py
        

📈 Output

• student_performance_6000.csv – Generated dataset
• filtered_output.csv – Filtered analysis results

🚀 Future Improvements

• Add data visualization using Matplotlib or Seaborn
• Implement grading and ranking system
• Create an interactive dashboard using Streamlit

Author: Jadwinder Singh