pandas.Series.add
Series.add(other, level=None, fill_value=None, axis=0)
Examples
>>> a = pd.Series([1, 1, 1, np.nan], index=['a', 'b', 'c', 'd'])
>>> a
a 1.0
b 1.0
c 1.0
d NaN
dtype: float64
>>> b = pd.Series([1, np.nan, 1, np.nan], index=['a', 'b', 'd', 'e'])
>>> b
a 1.0
b NaN
d 1.0
e NaN
dtype: float64
>>> a.add(b, fill_value=0)
a 2.0
b 1.0
c 1.0
d 1.0
e NaN
dtype: float64
From pandas 0.24.2 documentation
我没弄不明白参数fill_value具体咋样,然后查了一些资料
该参数使a中value的NaN=fill_value,然后与b中相同索引的value相加
注意:缺失值NaN与任何值相加的结果均为NaN,所以这就是为什么要用到fill_value的原因啦