python-比较pd.Series并在该系列不包含None时获得异常结果

我想知道为什么将两个相同的系列与None值进行比较会返回False：

pd.Series(['x', 'y', None]) == pd.Series(['x', 'y', None])

0     True
1     True
2    False
dtype: bool

我希望所有结果都是正确的.如果我从系列中创建一个数组,并进行比较,我将得到预期的结果：

pd.Series(['x', 'y', None]).values == pd.Series(['x', 'y', None]).values

array([ True,  True,  True])

为什么没有的两个相同的序列彼此不相等？我想念什么吗？

我希望np.nan会出现这种情况,因为np.nan！= np.nan;但是,无==无

解决方法:

这是by design：

see the warnings Box: 07001

This was done quite a while ago to make the behavior of nulls
consistent, in that they don’t compare equal. This puts None and
np.nan on an equal (though not-consistent with python, BUT consistent
with numpy) footing.

So this is not a bug, rather a consequence of sTradling 2 conventions.

I suppose the documentation Could be slightly enhanced.

要使包含空值的级数相等,请使用pd.Series.equals：

pd.Series(['x', 'y', None]).equals(pd.Series(['x', 'y', None]))  # True