def min(self, axis=None, skipna=True):
nv.validate_minmax_axis(axis)<EOL>return nanops.nanmin(self._values, skipna=skipna)<EOL>
Return the minimum value of the Index.

Parameters
----------
axis : {None}
    Dummy argument for consistency with Series
skipna : bool, default True

Returns
-------
scalar
    Minimum value.

See Also
--------
Index.max : Return the maximum value of the object.
Series.min : Return the minimum value in a Series.
DataFrame.min : Return the minimum values in a DataFrame.

Examples
--------
>>> idx = pd.Index([3, 2, 1])
>>> idx.min()
1

>>> idx = pd.Index(['c', 'b', 'a'])
>>> idx.min()
'a'

For a MultiIndex, the minimum is determined lexicographically.

>>> idx = pd.MultiIndex.from_product([('a', 'b'), (2, 1)])
>>> idx.min()
('a', 1)