code: def min(self, axis=None, skipna=True):
          
          nv.validate_minmax_axis(axis)
          return nanops.nanmin(self._values, skipna=skipna)
docs: 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)