The "Result Analysis" project is a Python-based software project aimed at analyzing and visualizing student result data from our college's result website. The project employs web scraping using the Selenium library to extract student IDs and their corresponding marks. Subsequently, the data is analyzed using Python's Pandas and Matplotlib libraries to derive meaningful insights.
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Web Scraping: We utilize the Selenium library to automate the process of extracting student data from our college's result website.
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Data Analysis: With Pandas, we perform in-depth data analysis, including calculating the average marks of students.
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Visualization: Matplotlib is employed to create visualizations that help us understand the data better. We generate bar charts to visualize the top 3 students with the highest marks and the bottom 3 students with the lowest marks.
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The project provides insights into the top 3 students with the highest marks and the 3 students with the lowest marks.
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Additionally, the project calculates and displays the average marks of all students.
Contributions to this project are welcome! Feel free to submit issues, suggest improvements, or even create pull requests.
We would like to express our gratitude to the open-source community for developing and maintaining the libraries used in this project. Special thanks to the Python community, Selenium, Pandas, and Matplotlib teams.