:py:mod:`ForeTiS.preprocess.StatisticalFeatures`
================================================

.. py:module:: ForeTiS.preprocess.StatisticalFeatures


Module Contents
---------------


Functions
~~~~~~~~~

.. autoapisummary::

   ForeTiS.preprocess.StatisticalFeatures.add_lagged_statistics
   ForeTiS.preprocess.StatisticalFeatures.add_current_statistics



.. py:function:: add_lagged_statistics(seasonal_periods, windowsize_lagged_statistics, seasonal_lags, df, columns_for_lags_rolling_mean)

   Function adding lagged and seasonal-lagged features to dataset

   :param seasonal_periods: seasonal_period used for seasonal-lagged features
   :param windowsize_lagged_statistics: size of window used for sales statistics
   :param seasonal_lags: seasonal lags to add of the features specified
   :param df: dataset for adding features
   :param columns_for_lags_rolling_mean: the columns where seasonal lagged rolling mean should be applied


.. py:function:: add_current_statistics(seasonal_periods, windowsize_current_statistics, df, columns_for_rolling_mean, columns_for_lags)

   Function adding rolling seasonal statistics

   :param seasonal_periods: seasonal_period used for seasonal rolling statistics
   :param windowsize_current_statistics: size of window used for feature statistics
   :param df: dataset for adding features
   :param columns_for_rolling_mean: the columns where the rolling mean should be applied
   :param columns_for_lags: the columns that should be lagged by one sample