This repository contains the solution to the Tunts.Rocks 2024 Challenge for Software Engineering.
The challenge involves creating an application in Python to analyze student performance based on exam scores and attendance.
The analysis includes calculating averages, determining student situations, and exploring correlations between variables.
Programming Language: Python
Libraries: Pandas, gspread (Google Sheets integration)
Collaboration Platform: Google Colab
Open the Google Colab notebook.
Run each cell in sequential order to execute the code.
Monitor the log lines and check the final results.
EngSoftTunts.csv: CSV file containing the student data after preprocessing.
EngSoftTunts.xlsx: Excel file used for initial data extraction.
Challenge_TuntsRocks_2024.ipynb: Jupyter notebook with the complete code.
You can access the drive using the access link:
https://drive.google.com/drive/folders/17F2mKCFjWcfTwhOPs0vLhHZNBYuxKiF1?usp=sharing
The analysis covers student situations based on exam scores and attendance.
A correlation matrix reveals relationships between variables.
Average absences and grades are analyzed for different student situations.
A significant number of students (10) went to the Final Exam, indicating a borderline performance between pass and fail.
Attendance is crucial, with 8 students failing due to absences.
Only 1 student failed due to low grades, suggesting overall good performance in exams.
The analysis highlights the importance of both attendance and exam performance in determining student situations.
Recommendations for improvement can be tailored based on specific patterns observed in the data.
Feel free to explore the notebook for a detailed walkthrough of the code and analysis!
🚀 Happy coding! 🚀