📊 EduStats: Academic Performance Analyzer

EduStats is an advanced Python project tailored to manage and analyze academic performance for students in the BUT RT program. With seamless Excel file handling, precise calculations, robust data validation, and visually intuitive graphs, it provides actionable insights to help track and improve results. 📈🎓

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✨ Key Features

📁 Automated File Management

• Verifies and organizes academic files (semestre.xlsx, notes_RT.xlsx) automatically.
• Creates or updates the notes_RT.xlsx file based on the semester structure.

✅ Enhanced Data Validation

• Checks for sufficient rows and columns in Excel files to ensure accurate processing.
• Logs warnings and errors to help identify and resolve data issues efficiently.

📊 Weighted Average Calculation

• Computes averages for each Teaching Unit (UE) using module coefficients and user-provided grades.

🎨 Dynamic Visualization

• Generates clear, color-coded graphs with performance thresholds for success, warnings, and failures.

🚀 Optimized Performance

• Reduces repetitive data access and improves overall execution efficiency.

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📂 File Requirements

1️⃣ semestre.xlsx

• Defines the semester structure with module names and coefficients.
• Must be placed in the Stats folder.

2️⃣ notes_RT.xlsx

• Stores the grades for each module.
• Created or updated automatically based on semestre.xlsx.

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🚀 Installation & Usage

1️⃣ Install Dependencies

Ensure Python is installed and required libraries are added:

pip install openpyxl matplotlib

2️⃣ Clone the Repository

git clone https://github.com/your-username/EduStats.git
cd EduStats

3️⃣ Prepare Files

• Place semestre.xlsx in the Stats folder.
• The program will create or update notes_RT.xlsx for you.

4️⃣ Run the Program

python main.py

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🎨 Graph Overview

The output graph highlights performance for each Teaching Unit (UE) using a color-coded system:

• ✅ Averages ≥ 10: Green bars indicate success.
• ⚠️ Averages between 8 and 10: Orange bars suggest potential retakes.
• ❌ Averages < 8: Red bars flag failure.

Threshold markers at 10 (pass) and 8 (retake) are included for clarity.

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🛠️ How It Works

Step 1: File Verification

• Ensures the Stats directory exists.
• Verifies the presence of semestre.xlsx.
• Creates or updates notes_RT.xlsx automatically.

Step 2: Data Management

• Extracts module names and coefficients from semestre.xlsx.
• Populates notes_RT.xlsx with a user-friendly structure for grade input.

Step 3: Data Validation

• Validates Excel sheets for sufficient data before proceeding.
• Logs any discrepancies or missing information for user awareness.

Step 4: Average Calculation

• Computes weighted averages for each UE, accounting for module coefficients and grades.

Step 5: Visual Results

• Displays a visually intuitive bar chart with performance thresholds and color-coded bars.

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💡 Troubleshooting

Common Issues

• Missing Files: Ensure semestre.xlsx is in the Stats folder. If notes_RT.xlsx is missing, the program will create it.
• Corrupted Files: Verify that semestre.xlsx and notes_RT.xlsx are valid Excel files.

Debugging Tools

• Detailed logging output helps identify and resolve issues efficiently.

If issues persist, check the program output for detailed error messages.

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🛡 Contributing

We welcome contributions! 🚀

• Report issues or bugs via GitHub Issues.
• Submit improvements as pull requests to enhance functionality.

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📜 License

This project is licensed under the MIT License. You are free to use, modify, and distribute it under the terms of this license. Refer to the LICENSE file for details.

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🎉 EduStats simplifies academic data management and empowers you to track your success. Start using it today! 😊