Using If/Truth Statements with pandas

pandas follows the numpy convention of raising an error when you try to convert something to a bool. This happens in a if or when using the boolean operations, and, or, or not. It is not clear what the result of

>>>if pd.Series([False, True, False]):
     ...

should be. Should it be True because it’s not zero-length? False because there are False values? It is unclear, so instead, pandas raises a ValueError:

>>> if pd.Series([False, True, False]):
    print("I was true")
Traceback
    ...
ValueError: The truth value of an array is ambiguous. Use a.empty, a.any() or a.all().

这种情况下的布尔运算存在歧义，python不知道该以pd.Series是否为空为判断是和否，还是以pd.Series中是否有False来判断是和否。