Abstract
Formula1 Datasets is an open-source Data Science project. Datasets & Analyses for Formula 1 World Championship. Hello everyone! You are viewing my repository, dedicated to Formula 1 World Championship which is one of the most prestigious motorsport discipline and is spectated by millions of people worldwide on live, TV or online sources. It is built using Jupyter Notebook, Python. Key capabilities include: 2019 - 2026 Season Race Results; 2019 - 2024 Season Race Calendar; 2019 - 2024 Season Drivers. The complete source code is publicly available on GitHub under the GNU General Public License v3.0, making it a useful reference for students building a Data Science mini project or final-year project.
1. Introduction
Hello everyone! You are viewing my repository, dedicated to Formula 1 World Championship which is one of the most prestigious motorsport discipline and is spectated by millions of people worldwide on live, TV or online sources.
As an experienced data scientist and have been following F1 for over two decades, I have high-level of passion to make datasets and enable analyses on drivers & teams with regards to their race results, qualifying results, plus other sessions throughout the seasons.
All these data are obtained from Formula 1 Official Web Site, plus EA & Codemasters F1 Games for driver ratings here.
2. Objective
Datasets & Analyses for Formula 1 World Championship
This project demonstrates how Jupyter Notebook, Python can be applied to a real-world Data Science problem.
3. Key Features / Modules
- 2019 - 2026 Season Race Results
- 2019 - 2024 Season Race Calendar
- 2019 - 2024 Season Drivers
- 2021 - 2024 Season Teams
- 2022 - 2026 Season Qualifying Results
- 2021, 2024 & 2025 Season Sprint Qualifying Results
- 2022 - 2025 Season Sprint Race Results
- 2023 Season Sprint Shootout Results
- 2022 - 2024 Season Driver of the Day Vote Results
- Driver Ratings from Codemasters F1 2020 Official Video Game
4. Technology Stack
5. System Requirements
General requirements for this technology stack — check the README for exact versions.
- Python 3.8 or later with Jupyter Notebook / JupyterLab (or Google Colab)
- pip for dependencies
- Python 3.8 or later
- pip / virtualenv for dependencies
- VS Code, PyCharm or Jupyter Notebook
- Git (to clone the repository)
6. Installation & Setup
git clone https://github.com/toUpperCase78/formula1-datasets.git
cd formula1-datasetsFull setup instructions are in the project README.
7. Future Enhancements
Suggested extensions you can add to make this your own project.
- Turn the analysis into an interactive dashboard
- Automate data refresh with a scheduled job
- Add a predictive model on top of the analysis
8. Viva / Review Questions
Common questions examiners ask for projects in this domain.
- What is the source of the dataset and how was missing data handled?
- Which exploratory analysis steps revealed the most useful insight?
- Why were these particular charts chosen to present the data?
- Which statistical or ML technique supports the conclusions?
- How could the analysis be automated or refreshed with new data?
9. Source Code & License
This project is developed by toUpperCase78 and published on GitHub under the GNU General Public License v3.0. Please follow the license terms and credit the original author when you use or modify this code.
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