sktime.datasets: Datasets

load_airline()

Load the airline univariate time series dataset [1].

load_arrow_head([split, return_X_y])

Loads the ArrowHead time series classification problem and returns X and y.

load_gunpoint([split, return_X_y])

Loads the GunPoint time series classification problem and returns X and y :param split: Whether to load the train or test partition of the problem. By default it loads both. :type split: None or str{“train”, “test”}, optional (default=None) :param return_X_y: If True, returns (features, target) separately instead of a single dataframe with columns for features and the target. :type return_X_y: bool, optional (default=False).

load_osuleaf([split, return_X_y])

Loads the OSULeaf time series classification problem and returns X and y

load_italy_power_demand([split, return_X_y])

Loads the ItalyPowerDemand time series classification problem and returns X and y

load_basic_motions([split, return_X_y])

Loads the BasicMotions time series classification problem and returns X and y.

load_japanese_vowels([split, return_X_y])

Loads the JapaneseVowels time series classification problem and returns X and y.

load_shampoo_sales()

Load the shampoo sales univariate time series dataset for forecasting.

load_longley([y_name])

Load the Longley multivariate time series dataset for forecasting with exogenous variables.

load_lynx()

Load the lynx univariate time series dataset for forecasting.

load_acsf1([split, return_X_y])

Loads the power consumption of typical appliances time series classification problem and returns X and y.

load_uschange([y_name])

Load the multivariate time series dataset for forecasting Growth rates of personal consumption and personal income.

load_UCR_UEA_dataset(name[, split, …])

Load dataset from UCR UEA time series classification repository.