docstr: Transform time series.
  
  Parameters
  ----------
  ts: pandas.Series or pandas.DataFrame
      Time series to be transformed. If a DataFrame with k columns, it is
      treated as k independent univariate time series.
  
      - If the transformer was trained with a Series, the transformer
        will be applied to each univariate series independently;
      - If the transformer was trained with a DataFrame, i.e. the
        transformer is essentially k transformers, those transformers
        will be applied to each univariate series respectively.
  
  Returns
  -------
  pandas.Series or pandas.DataFrame
      Transformed time series.
docstr_tok: ["Transform","time","series",".","Parameters","--","--","--","--","--","ts",":","pandas.Series","or","pandas.DataFrame","Time","series","to","be","transformed",".","If","a","DataFrame","with","k","columns",",","it","is","treated","as","k","independent","univariate","time","series",".","-","If","the","transformer","was","trained","with","a","Series",",","the","transformer","will","be","applied","to","each","univariate","series","independently",";","-","If","the","transformer","was","trained","with","a","DataFrame",",","i.e",".","the","transformer","is","essentially","k","transformers",",","those","transformers","will","be","applied","to","each","univariate","series","respectively",".","Returns","--","--","--","-","pandas.Series","or","pandas.DataFrame","Transformed","time","series","."]
code: def predict(
      self, ts: Union[pd.Series, pd.DataFrame]
  ) -> Union[pd.Series, pd.DataFrame]:
      """Transform time series.
  
      Parameters
      ----------
      ts: pandas.Series or pandas.DataFrame
          Time series to be transformed. If a DataFrame with k columns, it is
          treated as k independent univariate time series.
  
          - If the transformer was trained with a Series, the transformer
            will be applied to each univariate series independently;
          - If the transformer was trained with a DataFrame, i.e. the
            transformer is essentially k transformers, those transformers
            will be applied to each univariate series respectively.
  
      Returns
      -------
      pandas.Series or pandas.DataFrame
          Transformed time series.
  
      """
      return self._predict(ts)
  
file_path: adtk/src/adtk/_transformer_base.py
imports: from typing import Union
  import pandas
  from ._base import _NonTrainableMultivariateModel, _NonTrainableUnivariateModel, _TrainableMultivariateModel, _TrainableUnivariateModel
label_desc: Use image node_id 2 for calling the _TrainableUnivariateTransformer obj's underlying member method code with example usage: obj.predict(ts) and returns: self