'Center and scale the data.
Can be called on sparse input, provided that ``RobustScaler`` has been
fitted to dense input and ``with_centering=False``.
Parameters
X : {array-like, sparse matrix}
The data used to scale along the specified axis.'

def transform(self, X):

    if self.with_centering:
        check_is_fitted(self, 'center_')
    if self.with_scaling:
        check_is_fitted(self, 'scale_')
    X = self._check_array(X, self.copy)
    if sparse.issparse(X):
        if self.with_scaling:
            inplace_column_scale(X, (1.0 / self.scale_))
    else:
        if self.with_centering:
            X -= self.center_
        if self.with_scaling:
            X /= self.scale_
    return X
