code: def mask(self):
          
          if self.filter_func is None:
              raise RuntimeError("Can't get a mask without a filter function!")
          else:
              # only evaluate if no previous calculation was done
              if self._mask is None:
                  # get required columns into the namespace as numpy arrays
                  for column in self.columns:
                      if column in self.filter_func:
                          setattr(self, column, self.group[column][:])
                  self._mask = eval(self.filter_func)
              return self._mask
docs: Create a mask implementing the requested filter on the datasets
  
          Returns
          -------
          array of Boolean
              True for dataset indices to be returned by the get_column method