
The dataset is a comprehensive, structured collection of historical Formula 1 race data compiled from the Ergast API. It is organized in a relational format across multiple CSV files, each capturing a different aspect of the sport. The `races.csv` file includes metadata on each race such as date, circuit, and season. The `results.csv` file provides final race outcomes for every driver, while `qualifying.csv` contains qualifying session results. `lap_times.csv` and `pit_stops.csv` offer granular, session-level data for each driver’s performance throughout the race. Additional files such as `drivers.csv` and `constructors.csv` provide biographical and team-related information, while `constructor_standings.csv`, `driver_standings.csv`, and `constructor_results.csv` track season-long performance. Files like `circuits.csv`, `status.csv`, and `seasons.csv` provide supporting metadata that enhances the usability and relational structure of the dataset. This dataset is well-suited for time series analysis, predictive modeling, performance evaluation, and motorsport analytics.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
