CSCI 349 Final Project: Formula One Driver Performance Analysis

Team Members:

• Sean O'Connor
• Connor Coles

Project Summary

We are conducting a data mining project focused on analyzing driver performance in Formula One racing, with the goal to correlate driver performance with track and weather conditions, and to predict future race results using these correlations. We will apply various data mining techniques learned throughout the course to extract meaningful insights from the dataset.

Important Dates

• Data Selection Due: November 13, 2024
• DataPrep_EDA.ipynb Due: November 22, 2024
• Modeling.ipynb Due: December 4, 2024
• Final Report PDF Due: December 10, 2024
• Video Presentation Due: December 13, 2024

Package Structure

Directories:

• data - Contains the dataset used for analysis.
• notebooks - Contains Jupyter notebooks for data preparation, EDA, modeling, and the final report.

3rd Party Libraries

• pandas
• numpy
• matplotlib
• rapidfuzz
• fastf1

Video Presentation

Our video presentation will be linked here.

Final Deliverables

• DataPrep_EDA.ipynb - Notebook for data preparation and exploratory data analysis.
• Modeling.ipynb - Notebook for developing and evaluating predictive models.
• Final_Report.pdf - Comprehensive report summarizing our findings and methodologies, submitted to Gradescope.
• Video Presentation - A recorded video summarizing our project, linked above.

Important Links

• Dataset Source
• Dataset Documentation
• GitLab Repository