parameters: (self, axis=None, skipna=True, *args, **kwargs)
return_statement: return self._box_func(result)
docstring: Return the maximum value of the Array or maximum along
          an axis.
  
          See Also
          --------
          numpy.ndarray.max
          Index.max : Return the maximum value in an Index.
          Series.max : Return the maximum value in a Series.
docstring_summary: Return the maximum value of the Array or maximum along
          an axis.
docstring_tokens: Return the maximum value of the Array or maximum along an axis .
function: def max(self, axis=None, skipna=True, *args, **kwargs):
          """
          Return the maximum value of the Array or maximum along
          an axis.
  
          See Also
          --------
          numpy.ndarray.max
          Index.max : Return the maximum value in an Index.
          Series.max : Return the maximum value in a Series.
          """
          # TODO: skipna is broken with max.
          # See https://github.com/pandas-dev/pandas/issues/24265
          nv.validate_max(args, kwargs)
          nv.validate_minmax_axis(axis)
  
          mask = self.isna()
          if skipna:
              values = self[~mask].asi8
          elif mask.any():
              return NaT
          else:
              values = self.asi8
  
          if not len(values):
              # short-circut for empty max / min
              return NaT
  
          result = nanops.nanmax(values, skipna=skipna)
          # Don't have to worry about NA `result`, since no NA went in.
          return self._box_func(result)
function_tokens: def max ( self , axis = None , skipna = True , * args , * * kwargs ) : # TODO: skipna is broken with max. # See https://github.com/pandas-dev/pandas/issues/24265 nv . validate_max ( args , kwargs ) nv . validate_minmax_axis ( axis ) mask = self . isna ( ) if skipna : values = self [ ~ mask ] . asi8 elif mask . any ( ) : return NaT else : values = self . asi8 if not len ( values ) : # short-circut for empty max / min return NaT result = nanops . nanmax ( values , skipna = skipna ) # Don't have to worry about NA `result`, since no NA went in. return self . _box_func ( result )