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).

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.

dataset, predictionsTuple[Union[deepchecks.Dataset, pd.DataFrame], np.ndarray]

Tuple of the deepchecks dataset or dataframe and the predictions.