def get_result(self):
<EOL>if is_list_like(self.f) or is_dict_like(self.f):<EOL><INDENT>return self.obj.aggregate(self.f, axis=self.axis,<EOL>*self.args, **self.kwds)<EOL><DEDENT>if len(self.columns) == <NUM_LIT:0> and len(self.index) == <NUM_LIT:0>:<EOL><INDENT>return self.apply_empty_result()<EOL><DEDENT>if isinstance(self.f, str):<EOL><INDENT>func = getattr(self.obj, self.f)<EOL>sig = inspect.getfullargspec(func)<EOL>if '<STR_LIT>' in sig.args:<EOL><INDENT>self.kwds['<STR_LIT>'] = self.axis<EOL><DEDENT>return func(*self.args, **self.kwds)<EOL><DEDENT>elif isinstance(self.f, np.ufunc):<EOL><INDENT>with np.errstate(all='<STR_LIT:ignore>'):<EOL><INDENT>results = self.obj._data.apply('<STR_LIT>', func=self.f)<EOL><DEDENT>return self.obj._constructor(data=results, index=self.index,<EOL>columns=self.columns, copy=False)<EOL><DEDENT>if self.result_type == '<STR_LIT>':<EOL><INDENT>return self.apply_broadcast()<EOL><DEDENT>elif not all(self.obj.shape):<EOL><INDENT>return self.apply_empty_result()<EOL><DEDENT>elif self.raw and not self.obj._is_mixed_type:<EOL><INDENT>return self.apply_raw()<EOL><DEDENT>return self.apply_standard()<EOL>
compute the results