time_domain

Temporal feature transforms for time series data.

This module provides transforms that extract temporal features from datetime indices of time series datasets. These transforms add time-based features such as cyclic patterns, holiday indicators, and daylight information to enhance time series forecasting models.

Submodules

openstef_models.transforms.time_domain.cyclic_features_adder	Transform for extracting cyclic features from time series data.
openstef_models.transforms.time_domain.datetime_features_adder	Transform for extracting datetime-based features from time series data.
openstef_models.transforms.time_domain.holiday_features_adder	Transform that adds holiday features to time series data.
openstef_models.transforms.time_domain.lags_adder	Lag feature generation for time series forecasting.
openstef_models.transforms.time_domain.rolling_aggregates_adder	Transform for adding rolling aggregate features to time series data.
openstef_models.transforms.time_domain.versioned_lags_adder	Lag feature transforms for versioned time series data.

Classes

CyclicFeaturesAdder(**data)	Transform that generates cyclic temporal features from datetime indices.
DatetimeFeaturesAdder(**data)	Transform that adds datetime features to time series data.
HolidayFeatureAdder(**data)	Transform that adds holiday features to time series data.
LagsAdder(**data)	Transform that adds lag features to time series data.
RollingAggregatesAdder(**data)	Transform that adds rolling aggregate features to time series data.
VersionedLagsAdder(**data)	Create lag features while preserving data availability constraints.