Why does pandas “None | True” return False when Python “None or True” returns True?
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In pure Python, None or True returns True . However with pandas when I'm doing a | between two Series containing None values, results are not as I expected: >>> df.to_dict() {'buybox': {0: None}, 'buybox_y': {0: True}} >>> df buybox buybox_y 0 None True >>> df['buybox'] = (df['buybox'] | df['buybox_y']) >>> df buybox buybox_y 0 False True Expected result: >>> df buybox buybox_y 0 True True I get the result I want by applying the OR operation twice, but I don't get why I should do this. I'm not looking for a workaround (I have it by applying df['buybox'] = (df['buybox'] | df['buybox_y']) twice in a row) but a...