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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 _process(self, obj, key=None):
 """ Generates a categorical 2D aggregate by inserting NaNs at all cross-product locations that do not already have a value assigned. Returns a 2D gridded Dataset object. """

        if isinstance(obj, Dataset) and obj.interface.gridded:
            return obj
        elif obj.ndims > 2:
            raise ValueError("Cannot aggregate more than two dimensions")
        elif len(obj.dimensions()) < 3:
            raise ValueError("Must have at two dimensions to aggregate over"
                             "and one value dimension to aggregate on.")

        dtype = 'dataframe' if pd else 'dictionary'
        obj = Dataset(obj, datatype=[dtype])
        xcoords, ycoords = self._get_coords(obj)
        return self._aggregate_dataset(obj, xcoords, ycoords)