Welcome to the Student Performance Management System! This project is designed to manage a large dataset of student performance records, stored in MongoDB, through a user-friendly graphical interface developed with TKEnter.
The Student Performance dataset comprises approximately 300 rows and 15 attributes, covering various aspects of student performance. This system allows users to perform essential operations on the dataset, including insertion, deletion, updating, indexing, mapping, reducing, and selection.
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Graphical User Interface (GUI): Utilizes TKEnter to provide an intuitive and interactive interface for users to interact with the dataset.
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Data Manipulation: Allows users to perform CRUD (Create, Read, Update, Delete) operations on the dataset, ensuring efficient management and organization of student performance records.
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Database Integration: Seamlessly integrates with MongoDB using PyMongo to store and retrieve student performance data, enabling scalability and flexibility in handling large datasets.
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Advanced Operations: Supports advanced database operations such as indexing, mapping, reducing, and selective querying, empowering users with powerful data manipulation capabilities.
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Clone the repository:
git clone https://github.com/shimaamorsy/Student_Performance.git
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Ensure MongoDB and jupyter is installed and running locally.
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Run the application: run Performance.ipynb on jupyter
- Launch the application executing
Student Performance.ipynb. - Use the graphical interface to perform various operations on the student performance dataset.
- Enjoy seamless management and manipulation of student performance records!
Contributions are welcome! Please fork the repository, make your changes, and submit a pull request.
This project is licensed under the MIT License - see the LICENSE file for details.
student-performance, management-system, mongodb, tkenter, pymongo, gui, data-manipulation, `