SummaryTransformer

Calculate summary value of a time series.

Quickstart

from sktime.transformations.summarize import SummaryTransformer

estimator = SummaryTransformer(summary_function=('mean', 'std', 'min', 'max'), quantiles=(0.1, 0.25, 0.5, 0.75, 0.9), flatten_transform_index=True)

Parameters(3)

summary_functionstr, list, tuple, or None, default=(“mean”, “std”, “min”, “max”)

If not None, a string, or list or tuple of strings indicating the pandas summary functions that are used to summarize each column of the dataset. Must be one of (“mean”, “min”, “max”, “median”, “sum”, “skew”, “kurt”, “var”, “std”, “mad”, “sem”, “nunique”, “count”). If None, no summaries are calculated, and quantiles must be non-None.

quantilesstr, list, tuple or None, default=(0.1, 0.25, 0.5, 0.75, 0.9)

Optional list of series quantiles to calculate. If None, no quantiles are calculated, and summary_function must be non-None.

flatten_transform_indexbool, optional (default=True)

if True, columns of return DataFrame are flat, by “variablename__feature” if False, columns are MultiIndex (variablename__feature) has no effect if return mtype is one without column names

Examples

>>> from sktime.transformations.summarize import SummaryTransformer
>>> from sktime.datasets import load_airline
>>> y = load_airline ()
>>> transformer = SummaryTransformer ()
>>> y_mean = transformer. fit_transform (y)