This project analyzes ultramarathon trends from 2000 to 2022, focusing on performance metrics, participation rates, and the gender gap. The analysis aims to provide insights into how ultramarathon participation has evolved over the years and how performance metrics differ between male and female participants.
- Data Collection: Gathered data from various ultramarathon events over 22 years.
- Performance Analysis: Examined trends in finishing times and other performance indicators.
- Participation Analysis: Studied the growth in ultramarathon participation, with a focus on gender-based trends.
- Gender Gap Analysis: Investigated differences in performance and participation rates between male and female athletes.
- Statistical Analysis: Applied statistical methods and machine learning techniques, including linear regression, to analyze trends and predict future participation and performance metrics.
- Python: For data processing, analysis, and visualization.
- Jupyter Notebook: To develop and document the analysis interactively.
- Pandas & NumPy: For data manipulation and statistical analysis.
- Matplotlib & Seaborn: For creating visualizations to represent trends and insights.
- LaTeX: For generating the final report.
The analysis revealed key trends in ultramarathon participation and performance, which has been discussed in the report.
Created by Tanisha and Ishani. Feel free to reach out if you have any questions or suggestions!