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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 max(self, axis=None, skipna=True):
 """ Return the maximum value of the Index. Parameters axis : int, optional For compatibility with NumPy. Only 0 or None are allowed. skipna : bool, default True Returns ------- scalar Maximum value. See Also -------- Index.min : Return the minimum value in an Index. Series.max : Return the maximum value in a Series. DataFrame.max : Return the maximum values in a DataFrame. Examples -------- 3 'c' For a MultiIndex, the maximum is determined lexicographically. ('b', 2) """

        nv.validate_minmax_axis(axis)
        return nanops.nanmax(self._values, skipna=skipna)