load_data_and_predictions#
- load_data_and_predictions(data_format: str = 'Dataset', load_train: bool = True, modify_timestamps: bool = True, data_size: Optional[int] = 15000, random_state: int = 42) Tuple[Union[Dataset, DataFrame], ndarray][source]#
Load and returns the Airbnb NYC 2019 dataset (regression).
- Parameters
- data_formatstr , default: Dataset
Represent the format of the returned value. Can be ‘Dataset’|’Dataframe’ ‘Dataset’ will return the data as a Dataset object ‘Dataframe’ will return the data as a pandas Dataframe object
- load_trainbool , default: True
If True, the returned data is the train data. otherwise the test dataset.
- modify_timestampsbool , default: True
If True, the returned data timestamp column will be for the last 30 days. Otherwise, the data timestamp will be for March 2023.
- data_sizet.Optional[int] , default: 15000
The number of samples to return. If None, returns all the data.
- random_stateint , default 42
The random state to use for sampling.
- Returns
- ——-
- dataset, predictionsTuple[Union[deepchecks.Dataset, pd.DataFrame], np.ndarray]
Tuple of the deepchecks dataset or dataframe and the predictions.