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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 reduce(self, values, operator=np.add, axis=0, dtype=None):
 """Reduce the values over identical key groups, using the given ufunc reduction is over the first axis, which should have elements corresponding to the keys all other axes are treated indepenently for the sake of this reduction Parameters values to perform reduction over operator : numpy.ufunc a numpy ufunc, such as np.add or np.sum axis : int, optional the axis to reduce over dtype : output dtype Returns ------- values reduced by operator over the key-groups """

        values = np.take(values, self.index.sorter, axis=axis)
        return operator.reduceat(values, self.index.start, axis=axis, dtype=dtype)