Welcome to my portfolio! Here you will find information about my personal project focused on the University Running Competition called "CorriBicocca." In this project, I performed exploratory analysis on the results from previous years to gain insights into the performance of participants and schedule specific training accordingly.
CorriBicocca Exploratory Analysis is a personal project that I developed to analyze the results from previous editions of the University Running Competition called "CorriBicocca." As a participant in this run, I wanted to improve my training strategy by understanding the historical performance of participants. Therefore, I gathered data from the official CorriBicocca website and conducted a thorough analysis to uncover valuable insights.
- Exploratory Analysis: I performed in-depth exploratory analysis on the CorriBicocca dataset, which included data from the past five editions of the run. By examining factors such as race distances, completion times, participant demographics, and age groups, I gained a comprehensive understanding of the overall performance trends.
- Visualization: To present the analysis results effectively, I created interactive visualizations such as bar charts, scatter plots, and histograms. These visual representations allowed me to convey complex information in a clear and intuitive manner.
- Year-to-Year Comparison: By comparing the results across different editions of CorriBicocca, I identified patterns and changes in performance over time. This analysis helped me identify areas for improvement and set realistic goals for my own training.
- Training Schedule: Based on the insights gained from the analysis, I developed a training schedule tailored to my specific needs. I shared this schedule with my friends who also participated in the run, and it helped us optimize our training routines.
The CorriBicocca Exploratory Analysis project had a significant impact on my training and performance in the University Running Competition. By understanding the historical trends and patterns, I was able to make informed decisions about my training regimen and set realistic goals. This project not only improved my personal performance but also benefited my friends who participated in the run.
- Python
- Pandas
- Matplotlib
- Seaborn
- Streamlit
The CorriBicocca Exploratory Analysis project allowed me to dive deep into the data from previous editions of the University Running Competition. Through careful analysis, visualization, and the development of a tailored training schedule, I was able to improve my own performance and assist my friends in achieving their running goals. This project showcases my skills in data analysis, visualization, and the ability to derive meaningful insights from data.
If you have any questions or would like to learn more about this project, feel free to reach out to me.
Dashboard available at: http://corribicoccaresults.herokuapp.com