metadata
dataset_info:
features:
- name: Time
dtype: duration[ns]
- name: Driver
dtype: string
- name: DriverNumber
dtype: string
- name: LapTime
dtype: duration[ns]
- name: LapNumber
dtype: float64
- name: Stint
dtype: float64
- name: PitOutTime
dtype: duration[ns]
- name: PitInTime
dtype: duration[ns]
- name: Sector1Time
dtype: duration[ns]
- name: Sector2Time
dtype: duration[ns]
- name: Sector3Time
dtype: duration[ns]
- name: Sector1SessionTime
dtype: duration[ns]
- name: Sector2SessionTime
dtype: duration[ns]
- name: Sector3SessionTime
dtype: duration[ns]
- name: SpeedI1
dtype: float64
- name: SpeedI2
dtype: float64
- name: SpeedFL
dtype: float64
- name: SpeedST
dtype: float64
- name: IsPersonalBest
dtype: bool
- name: Compound
dtype: string
- name: TyreLife
dtype: float64
- name: FreshTyre
dtype: bool
- name: Team
dtype: string
- name: LapStartTime
dtype: duration[ns]
- name: LapStartDate
dtype: timestamp[ns]
- name: TrackStatus
dtype: string
- name: Position
dtype: float64
- name: Deleted
dtype: bool
- name: DeletedReason
dtype: string
- name: FastF1Generated
dtype: bool
- name: IsAccurate
dtype: bool
- name: DistanceToDriverAhead
sequence:
sequence: float64
- name: RPM
sequence:
sequence: float64
- name: Speed
sequence:
sequence: float64
- name: nGear
sequence:
sequence: float64
- name: Throttle
sequence:
sequence: float64
- name: Brake
sequence:
sequence: float64
- name: DRS
sequence:
sequence: float64
- name: X
sequence:
sequence: float64
- name: 'Y'
sequence:
sequence: float64
- name: Z
sequence:
sequence: float64
- name: gear_vis
dtype: image
- name: speed_vis
dtype: image
- name: RPM_emb
sequence: float64
- name: Speed_emb
sequence: float64
- name: nGear_emb
sequence: float64
- name: Throttle_emb
sequence: float64
- name: Brake_emb
sequence: float64
- name: X_emb
sequence: float64
- name: Y_emb
sequence: float64
- name: Z_emb
sequence: float64
- name: portrait
dtype: image
splits:
- name: train
num_bytes: 561415487.5469999
num_examples: 1317
download_size: 300522146
dataset_size: 561415487.5469999
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
Dataset Card for "f1_dataset"
This dataset includes race telemetry data from the Formula1 Montreail 2023 GP. It was obtained from the Ergast API using the fastf1 library.
We built an interactive demo for this dataset on Hugging Face spaces.
You can explore the dataset on your machine with Spotlight:
pip install renumics-spotlight
import datasets
from renumics import spotlight
ds = datasets.load_dataset('renumics/f1_dataset', split='train')
dtypes = {"DistanceToDriverAhead": spotlight.Sequence1D, "RPM": spotlight.Sequence1D, "Speed": spotlight.Sequence1D, "nGear": spotlight.Sequence1D,
"Throttle": spotlight.Sequence1D, "Brake": spotlight.Sequence1D, "DRS": spotlight.Sequence1D, "X": spotlight.Sequence1D, "Y": spotlight.Sequence1D, "Z": spotlight.Sequence1D,
'RPM_emb': spotlight.Embedding, 'Speed_emb': spotlight.Embedding, 'nGear_emb': spotlight.Embedding, 'Throttle_emb': spotlight.Embedding, 'Brake_emb': spotlight.Embedding,
'X_emb': spotlight.Embedding, 'Y_emb': spotlight.Embedding, 'Z_emb': spotlight.Embedding}
spotlight.show(ds, dtype=dtypes)