class_docstr: Create exogeneous features which are a copy of the endogenous data.
  
  Replaces exogeneous features (`X`) by endogeneous data (`y`).
  
  To *add* instead of *replace*, use `FeatureUnion`.
  
  Parameters
  ----------
  subset_index : boolean, optional, default=False
      if True, subsets the output of `transform` to `X.index`,
      i.e., outputs `y.loc[X.index]`
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docstr: Inverse transform, inverse operation to transform.
  
  Drops featurized column that was added in transform().
  
  Parameters
  ----------
  X : Series or Panel of mtype X_inner_mtype
      if X_inner_mtype is list, _inverse_transform must support all types in it
      Data to be inverse transformed
  y : Series or Panel of mtype y_inner_mtype, optional (default=None)
      Additional data, e.g., labels for transformation
  
  Returns
  -------
  inverse transformed version of X
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code: def _inverse_transform(self, X, y=None):
      """Inverse transform, inverse operation to transform.
  
      Drops featurized column that was added in transform().
  
      Parameters
      ----------
      X : Series or Panel of mtype X_inner_mtype
          if X_inner_mtype is list, _inverse_transform must support all types in it
          Data to be inverse transformed
      y : Series or Panel of mtype y_inner_mtype, optional (default=None)
          Additional data, e.g., labels for transformation
  
      Returns
      -------
      inverse transformed version of X
      """
      if self.subset_index:
          return y.loc[X.index.intersection(y.index)]
      else:
          return y
  
imports: from sktime.transformations.base import BaseTransformer
label_desc: Use image node_id 3 for calling the YtoX obj's underlying member method code with example usage: obj._inverse_transform(X, y) and returns: y, y