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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, data, centers=None):
 """ Find entries of all hypercubes. If `centers=None`, then use `self.centers_` as computed in `self.fit`. Empty hypercubes are removed from the result Parameters =========== data: array-like Data to find in entries in cube. Warning: first column must be index column. centers: list of array-like Center points for all cubes as returned by `self.fit`. Default is to use `self.centers_`. Returns ========= hypercubes: list of array-like list of entries in each hypercobe in `data`. """


        centers = centers or self.centers_
        hypercubes = [
            self.transform_single(data, cube, i) for i, cube in enumerate(centers)
        ]

        # Clean out any empty cubes (common in high dimensions)
        hypercubes = [cube for cube in hypercubes if len(cube)]
        return hypercubes