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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def transform(self, X):
 """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. This implementation was copied and modified from Scikit-Learn. See License information here: https://github.com/scikit-learn/scikit-learn/blob/master/README.rst """

        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