parameters: (self, axis=None, skipna=True, *args, **kwargs)
return_statement: return nanops.nanargmax(self._values, skipna=skipna)
docstring: Return an ndarray of the maximum argument indexer.
  
          Parameters
          ----------
          axis : {None}
              Dummy argument for consistency with Series.
          skipna : bool, default True
  
          Returns
          -------
          numpy.ndarray
              Indices of the maximum values.
  
          See Also
          --------
          numpy.ndarray.argmax
docstring_summary: Return an ndarray of the maximum argument indexer.
docstring_tokens: Return an ndarray of the maximum argument indexer .
function: def argmax(self, axis=None, skipna=True, *args, **kwargs):
          """
          Return an ndarray of the maximum argument indexer.
  
          Parameters
          ----------
          axis : {None}
              Dummy argument for consistency with Series.
          skipna : bool, default True
  
          Returns
          -------
          numpy.ndarray
              Indices of the maximum values.
  
          See Also
          --------
          numpy.ndarray.argmax
          """
          nv.validate_minmax_axis(axis)
          nv.validate_argmax_with_skipna(skipna, args, kwargs)
          return nanops.nanargmax(self._values, skipna=skipna)
function_tokens: def argmax ( self , axis = None , skipna = True , * args , * * kwargs ) : nv . validate_minmax_axis ( axis ) nv . validate_argmax_with_skipna ( skipna , args , kwargs ) return nanops . nanargmax ( self . _values , skipna = skipna )