class_docstr: Delegator mixin that delegates all methods to wrapped transformer.
  
  Delegates inner transformer methods to a wrapped estimator.
      Wrapped estimator is value of attribute with name self._delegate_name.
      By default, this is "estimator_", i.e., delegates to self.estimator_
      To override delegation, override _delegate_name attribute in child class.
  
  Delegates the following inner underscore methods:
      _fit, _transform, _inverse_transform, _update
  
  Does NOT delegate get_params, set_params.
      get_params, set_params will hence use one additional nesting level by default.
  
  Does NOT delegate or copy tags, this should be done in a child class if required.
docstr: Use wrapped transformer to transform X and return a transformed version.
  
  Parameters
  ----------
  X : Series or Panel, any supported mtype
      Data to be transformed, of python type as follows:
          Series: pd.Series, pd.DataFrame, or np.ndarray (1D or 2D)
          Panel: pd.DataFrame with 2-level MultiIndex, list of pd.DataFrame,
              nested pd.DataFrame, or pd.DataFrame in long/wide format
          subject to sktime mtype format specifications, for further details see
              examples/AA_datatypes_and_datasets.ipynb
  y : Series or Panel, default=None
      Additional data, e.g., labels for transformation
  
  Returns
  -------
  transformed version of X
  type depends on type of X and scitype:transform-output tag:
      |          | `transform`  |                        |
      |   `X`    |  `-output`   |     type of return     |
      |----------|--------------|------------------------|
      | `Series` | `Primitives` | `pd.DataFrame` (1-row) |
      | `Panel`  | `Primitives` | `pd.DataFrame`         |
      | `Series` | `Series`     | `Series`               |
      | `Panel`  | `Series`     | `Panel`                |
      | `Series` | `Panel`      | `Panel`                |
  instances in return correspond to instances in `X`
  combinations not in the table are currently not supported
  
  Explicitly, with examples:
      if `X` is `Series` (e.g., `pd.DataFrame`) and `transform-output` is `Series`
          then the return is a single `Series` of the same mtype
          Example: detrending a single series
      if `X` is `Panel` (e.g., `pd-multiindex`) and `transform-output` is `Series`
          then the return is `Panel` with same number of instances as `X`
              (the transformer is applied to each input Series instance)
          Example: all series in the panel are detrended individually
      if `X` is `Series` or `Panel` and `transform-output` is `Primitives`
          then the return is `pd.DataFrame` with as many rows as instances in `X`
          Example: i-th row of the return has mean and variance of the i-th series
      if `X` is `Series` and `transform-output` is `Panel`
          then the return is a `Panel` object of type `pd-multiindex`
          Example: i-th instance of the output is the i-th window running over `X`
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code: def _transform(self, X, y=None):
      """Use wrapped transformer to transform X and return a transformed version.
  
      Parameters
      ----------
      X : Series or Panel, any supported mtype
          Data to be transformed, of python type as follows:
              Series: pd.Series, pd.DataFrame, or np.ndarray (1D or 2D)
              Panel: pd.DataFrame with 2-level MultiIndex, list of pd.DataFrame,
                  nested pd.DataFrame, or pd.DataFrame in long/wide format
              subject to sktime mtype format specifications, for further details see
                  examples/AA_datatypes_and_datasets.ipynb
      y : Series or Panel, default=None
          Additional data, e.g., labels for transformation
  
      Returns
      -------
      transformed version of X
      type depends on type of X and scitype:transform-output tag:
          |          | `transform`  |                        |
          |   `X`    |  `-output`   |     type of return     |
          |----------|--------------|------------------------|
          | `Series` | `Primitives` | `pd.DataFrame` (1-row) |
          | `Panel`  | `Primitives` | `pd.DataFrame`         |
          | `Series` | `Series`     | `Series`               |
          | `Panel`  | `Series`     | `Panel`                |
          | `Series` | `Panel`      | `Panel`                |
      instances in return correspond to instances in `X`
      combinations not in the table are currently not supported
  
      Explicitly, with examples:
          if `X` is `Series` (e.g., `pd.DataFrame`) and `transform-output` is `Series`
              then the return is a single `Series` of the same mtype
              Example: detrending a single series
          if `X` is `Panel` (e.g., `pd-multiindex`) and `transform-output` is `Series`
              then the return is `Panel` with same number of instances as `X`
                  (the transformer is applied to each input Series instance)
              Example: all series in the panel are detrended individually
          if `X` is `Series` or `Panel` and `transform-output` is `Primitives`
              then the return is `pd.DataFrame` with as many rows as instances in `X`
              Example: i-th row of the return has mean and variance of the i-th series
          if `X` is `Series` and `transform-output` is `Panel`
              then the return is a `Panel` object of type `pd-multiindex`
              Example: i-th instance of the output is the i-th window running over `X`
      """
      estimator = self._get_delegate()
      return estimator.transform(X, y=y)
  
file_path: sktime/sktime/transformations/_delegate.py
imports: from sktime.transformations.base import BaseTransformer
label_desc: Use image node_id 3 for calling the _DelegatedTransformer obj's underlying member method code with example usage: obj._transform(X, y) and returns: estimator