An R package to access Formula 1 Data from the Ergast API and the official F1 data stream via the fastf1 python library.
if (!require("remotes")) install.packages("remotes")
remotes::install_github("SCasanova/f1dataR")Data is pulled from:
load_laps(season = 'current', race = 'last') This function loads
lap-by-lap time data for all drivers in a given season and round. Round
refers to race number. The defaults are current season and last race.
Lap data is limited to 1996-present.
Example:
library(f1dataR)
#> Loading required package: reticulate
load_laps()
#> # A tibble: 953 × 6
#> driverId position time lap time_sec season
#> <chr> <chr> <chr> <int> <dbl> <dbl>
#> 1 leclerc 1 1:43.351 1 103. 2022
#> 2 max_verstappen 2 1:44.415 1 104. 2022
#> 3 hamilton 3 1:45.421 1 105. 2022
#> 4 perez 4 1:46.399 1 106. 2022
#> 5 alonso 5 1:47.416 1 107. 2022
#> 6 russell 6 1:47.996 1 108. 2022
#> 7 norris 7 1:48.540 1 109. 2022
#> 8 ricciardo 8 1:49.249 1 109. 2022
#> 9 ocon 9 1:50.622 1 111. 2022
#> 10 stroll 10 1:51.666 1 112. 2022
#> # … with 943 more rowsor
load_laps(2021, 15)
#> # A tibble: 1,000 × 6
#> driverId position time lap time_sec season
#> <chr> <chr> <chr> <int> <dbl> <dbl>
#> 1 sainz 1 1:42.997 1 103. 2021
#> 2 norris 2 1:44.272 1 104. 2021
#> 3 russell 3 1:46.318 1 106. 2021
#> 4 stroll 4 1:47.279 1 107. 2021
#> 5 ricciardo 5 1:48.221 1 108. 2021
#> 6 alonso 6 1:49.347 1 109. 2021
#> 7 hamilton 7 1:49.826 1 110. 2021
#> 8 perez 8 1:50.617 1 111. 2021
#> 9 ocon 9 1:51.098 1 111. 2021
#> 10 raikkonen 10 1:51.778 1 112. 2021
#> # … with 990 more rowsget_driver_telemetry(season = 'current', race = 'last', session = 'R', driver, fastest_only = FALSE)
When the parameters for season (four digit year), race (number or GP name), session (FP1. FP2, FP3, Q or R), and driver code (three letter code) are entered, the function will load all data for a session and the pull the info for the selected driver. The first time a session is called, loading times will be relatively long but in subsequent calls this will improve to only a couple of seconds
get_driver_telemetry(2022, 4, driver = 'PER')
#> The first time a session is loaded, some time is required. Please be patient. Subsequent times will be faster
#> # A tibble: 42,415 × 19
#> Date SessionTime DriverAhead DistanceToDriverAhead
#> <dttm> <dttm> <chr> <dbl>
#> 1 2022-04-24 08:03:03 NA "" 0.0889
#> 2 2022-04-24 08:03:03 NA "" 0.0889
#> 3 2022-04-24 08:03:03 NA "" 0.0889
#> 4 2022-04-24 08:03:03 NA "6" 0.0889
#> 5 2022-04-24 08:03:03 NA "6" 0.0593
#> 6 2022-04-24 08:03:03 NA "6" 0.0296
#> 7 2022-04-24 08:03:03 NA "77" 0
#> 8 2022-04-24 08:03:04 NA "77" 0.0222
#> 9 2022-04-24 08:03:04 NA "6" 0.0444
#> 10 2022-04-24 08:03:04 NA "6" 0.0444
#> # … with 42,405 more rows, and 15 more variables: Time <dttm>, RPM <dbl>,
#> # Speed <dbl>, nGear <dbl>, Throttle <dbl>, Brake <lgl>, DRS <dbl>,
#> # Source <chr>, RelativeDistance <dbl>, Status <chr>, …
get_driver_telemetry(2018, 7,'Q', 'HAM', fastest_only = T)
#> The first time a session is loaded, some time is required. Please be patient. Subsequent times will be faster
#> # A tibble: 534 × 19
#> Date SessionTime DriverAhead DistanceToDriverAhead
#> <dttm> <dttm> <chr> <dbl>
#> 1 2018-06-09 13:59:18 NA "" 383.
#> 2 2018-06-09 13:59:18 NA "" 383.
#> 3 2018-06-09 13:59:18 NA "" 383.
#> 4 2018-06-09 13:59:19 NA "7" 383.
#> 5 2018-06-09 13:59:19 NA "7" 379.
#> 6 2018-06-09 13:59:19 NA "7" 375.
#> 7 2018-06-09 13:59:19 NA "7" 370.
#> 8 2018-06-09 13:59:19 NA "7" 366.
#> 9 2018-06-09 13:59:19 NA "7" 362.
#> 10 2018-06-09 13:59:19 NA "7" 358.
#> # … with 524 more rows, and 15 more variables: Time <dttm>, RPM <dbl>,
#> # Speed <dbl>, nGear <dbl>, Throttle <dbl>, Brake <lgl>, DRS <dbl>,
#> # Source <chr>, RelativeDistance <dbl>, Status <chr>, …load_pitstops(season = 'current', race ='last')load_drivers(season = 2022)load_schedule(season = 2022)load_standings(season = 'current', round = 'last', type = c('driver', 'constructor'))load_results(season = 'current', round = 'last')load_quali(season = 'current', round = 'last')plot_fastest(season = 'current', race = 'last', driver, color = 'gear')
clear_f1_cache() Clears the cache for all functions in the package.
The package also includes a static data frame for all current drivers and their respective constructors. Complete with team colors, logo and driver number logo.
driver_constructor_data %>% colnames()
#> [1] "driverId" "fullName" "driverCode"
#> [4] "constructorId" "constructorName" "constructorColor"
#> [7] "constructorColor2" "constructorLogo" "driverNumber"
#> [10] "numberImage" "season"