https://github.com/mihaildoman/formula-one-insights-with-python-and-sql

Using Python and SQL to analyze the achievements of drivers and constructors throughout Formula One's history.
https://github.com/mihaildoman/formula-one-insights-with-python-and-sql

data data-analysis data-visualization formula-one formula1

Last synced: 4 days ago
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Using Python and SQL to analyze the achievements of drivers and constructors throughout Formula One's history.

• Host: GitHub
• URL: https://github.com/mihaildoman/formula-one-insights-with-python-and-sql
• Owner: mihaildoman
• License: mit
• Created: 2025-01-17T19:22:14.000Z (12 days ago)
• Default Branch: main
• Last Pushed: 2025-01-18T07:52:38.000Z (12 days ago)
• Last Synced: 2025-01-18T08:30:49.572Z (12 days ago)
• Topics: data, data-analysis, data-visualization, formula-one, formula1
• Language: Jupyter Notebook
• Homepage:
• Size: 17.7 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

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README

        
# Formula One Insights with Pyton & SQL

Rising from the legacy of the interwar drivers' championships, [Formula One](https://en.wikipedia.org/wiki/Formula_One) officially began with the 1950 British Grand Prix at Silverstone, marking the first-ever world championship race. Since its inception, the sport has stood as the pinnacle of global motorsport, continuously pushing the boundaries of racing and automotive engineering.

As the highest class of international racing, Formula One is governed by a dynamic set of regulations - the formula - that all participants must adhere to. The sport spans continents, hosting races on purpose-built circuits and closed public roads, bringing the thrill of competition to audiences worldwide.

Over the decades, Formula One has captivated fans with legendary races, iconic drivers and teams who have tested the limits of human skill and technological innovation. 

This analysis leverages Python and SQL to uncover key insights into the achievements of drivers and constructors throughout F1’s storied history.

## The repository includes the following components:

- Five Jupyter Notebooks dedicated to retrieving, preprocessing, and visualizing Formula One data.

- A PDF presentation offering an in-depth analysis and interpretation of the results.

- Datasets sourced from the [formula1.com](https://formula1.com) website and [F1DB](https://github.com/f1db/f1db).

- An SQLite database used to centralize the data for structured storage and efficient querying.

- Custom datasets generated using Jupyter for analytical purposes.

- Charts and maps created in Jupyter to support our analysis.