(self, X, y=None)
return self.fit_transform(X, y)
Alias for :meth:`fit_transform`.

        Allows for this class to be used as an intermediate step in a
        scikit-learn pipeline.

        Parameters
        ----------
        X : list of length n_samples, or ndarray of shape (n_samples, ...)
            Collection of inputs to be fit-transformed by `transformer`.

        y : None
            There is no need for a target in a transformer, yet the pipeline
            API requires this parameter.

        Returns
        -------
        Xt : list of length n_samples, or ndarray of shape (n_samples, ...)
            Collection of outputs. It is a list unless all outputs have the
            same shape, in which case it is converted to an ndarray.
Alias for :meth:`fit_transform`.
Alias for : meth : fit_transform .
def transform(self, X, y=None):
        """Alias for :meth:`fit_transform`.

        Allows for this class to be used as an intermediate step in a
        scikit-learn pipeline.

        Parameters
        ----------
        X : list of length n_samples, or ndarray of shape (n_samples, ...)
            Collection of inputs to be fit-transformed by `transformer`.

        y : None
            There is no need for a target in a transformer, yet the pipeline
            API requires this parameter.

        Returns
        -------
        Xt : list of length n_samples, or ndarray of shape (n_samples, ...)
            Collection of outputs. It is a list unless all outputs have the
            same shape, in which case it is converted to an ndarray.

        """
        return self.fit_transform(X, y)
def transform ( self , X , y = None ) : return self . fit_transform ( X , y )