This project performs an end-to-end exploratory data analysis (EDA) on historical (F1) data spanning 1950 to 2022.
The analysis focuses on driver performance, constructor dominance, era-wise trends, and championship patterns using Python.
The objective is to uncover long-term performance insights and understand how dominance and competition in Formula One have evolved across decades.
Original Dataset Link -- https://www.kaggle.com/datasets/mustafatomak/formula-1-dataset-1950-2021
- Analyse the historical performance of drivers and constructors
- Identify dominant eras in Formula One history
- Compare driver consistency vs peak performance
- Study championship trends over time
- Derive insights from long-term motorsport data
- What matters more, the driver or the Constructor?
The analysis utilises multiple interrelated datasets spanning Formula One's history.
- Drivers – career statistics, wins, podiums
- Constructors – team performance and championships
- Races – season-wise and race-level results
- Seasons: 1950 – 2022
- Granularity:
- Season-level summaries
- Race-level performance data
📌 The dataset structure enables relational and time-series analysis.
- Python
- Pandas
- NumPy
- Visualization
- PowerBI
- Jupyter Notebook
- Dataset relationships and joins
- Row and column analysis across tables
- Understanding historical data consistency
- Inspection of missing and legacy values
Key steps performed:
- Standardised driver and constructor names
- Handled missing or legacy-era records
- Filtered incomplete seasons where required
- Ensured consistent data types across datasets
- Merged datasets for unified analysis
- Aggregated wins, podiums, and points
- Created era-based groupings (decades)
- Calculated championship conversion metrics
- Derived consistency indicators across seasons
- Career wins and podiums
- Championship counts
- Longevity vs success comparison
- Team dominance across eras
- Constructor championships over time
- Competitive cycles and transitions
- Dominant teams per decade
- Changes in competition intensity
- Shifts in championship concentration
- Repeat champions vs one-time winners
- Era-based dominance trends
- Performance distribution across teams
- Formula One history is marked by distinct eras of dominance
- A small number of constructors account for a majority of championships
- Driver longevity does not always correlate with championship success
- Competitive balance varies significantly across decades
📦 formula-one-data-analysis ┣ 📂 data ┃ ┣ drivers.csv ┃ ┣ constructor.csv ┃ ┣ race.csv ┣ 📂 notebooks ┃ ┗ constructor.ipynb ┃ ┗ driver.ipynb ┃ ┗ race.ipynb ┣ 📄 README.md ┣ 📄 requirements.txt ┗ 📄 .gitignore