Project Overview
This final project integrates multiple phases of data analysis: automated data collection, parsing, and visualization.
Key research questions were addressed through the empirical analysis of performance data.
Key Components
- Data Source: Collected performance data using web scraping and APIs.
- Crawler: Implemented an automated crawler to fetch HTML data.
- Parser: Extracted structured data from HTML tables.
- Analysis: Visualized trends using histograms, scatter plots, and multi-panel figures.
Key Results
- Generated probability distributions to analyze data patterns.
- Identified significant correlations using scatter plots.
- Discussed limitations, challenges, and potential improvements.
Tools Used
- Python
- BeautifulSoup
- Pandas
- Matplotlib
- NumPy
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Explore the detailed implementation, including source code and visualizations, on GitHub:
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