Method fit_transform

sklearn/preprocessing/_data.py:3390–3407

Fit `PowerTransformer` to `X`, then transform `X`. Parameters ---------- X : array-like of shape (n_samples, n_features) The data used to estimate the optimal transformation parameters and to be transformed using a power transformation. y : I

(self, X, y=None)

    @_fit_context(prefer_skip_nested_validation=True)
    def fit_transform(self, X, y=None):
        """Fit `PowerTransformer` to `X`, then transform `X`.

        Parameters
        ----------
        X : array-like of shape (n_samples, n_features)
            The data used to estimate the optimal transformation parameters
            and to be transformed using a power transformation.

        y : Ignored
            Not used, present for API consistency by convention.

        Returns
        -------
        X_new : ndarray of shape (n_samples, n_features)
            Transformed data.
        """
        return self._fit(X, y, force_transform=True)

    def _fit(self, X, y=None, force_transform=False):
        X = self._check_input(X, in_fit=True, check_positive=True)