We do allow using logical operators like | to be used with non-boolean data (at which point the non-bool series would be cast to bool, I assume). For example:
>>> ser1 = pd.Series([False, False]) >>> ser2 = pd.Series([0.0, 0.1]) >>> ser1 | ser2 0 False 1 True dtype: bool
This also worked with strings in object dtype:
>>> ser2 = pd.Series(["", "b"], dtype=object) >>> ser1 | ser2 0 False 1 True dtype: bool
but currently fails with the pyarrow-backed string dtype:
>>> pd.options.future.infer_string = True
>>> ser2 = pd.Series(["", "b"])
>>> ser1 | ser2
...
File ~/scipy/repos/pandas/pandas/core/arrays/arrow/array.py:833, in ArrowExtensionArray._logical_method(self, other, op)
831 return self._evaluate_op_method(other, op, ARROW_BIT_WISE_FUNCS)
832 else:
--> 833 return self._evaluate_op_method(other, op, ARROW_LOGICAL_FUNCS)
File ~/scipy/repos/pandas/pandas/core/arrays/arrow/array.py:824, in ArrowExtensionArray._evaluate_op_method(self, other, op, arrow_funcs)
822 result = pc_func(self._pa_array, other)
823 except pa.ArrowNotImplementedError as err:
--> 824 raise TypeError(self._op_method_error_message(other_original, op)) from err
825 return type(self)(result)
TypeError: operation 'ror_' not supported for dtype 'str' with dtype 'bool'
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