Python DolphinDB中索引对齐的熊猫式操作

在pandas中，如果我对具有不同索引的两个数据帧或序列执行二进制操作，它们的索引将对齐，具有相同索引值的行的计算如下：

>>> s1 = pd.Series([1,2,3,4], index=["a","a","b","c"])
>>> s2 = pd.Series([10,20,30,40], index=["a","a","a","c"])
>>> s1 + s2
a    11.0
a    21.0
a    31.0
a    12.0
a    22.0
a    32.0
b     NaN
c    44.0
dtype: float64

我想知道如何在DolphinDB中执行索引对齐操作，例如：

s1 = table([1,2,3,4] as val, ["a","a","b","c"] as index)
s2 = table([10,20,30,40] as val, ["a","a","a","c"] as index)

// How do I do an index-aligned add operation?

---

您可以使用DolphinDB Orca API

import dolphindb.orca as orca
s1=orca.Series([1,2,3,4], index=["a","a","b","c"])
s2=orca.Series([10,20,30,40], index=["a","a","a","c"])
s1+s2
>>> s1+s2
a    11.0
a    21.0
a    31.0
a    12.0
a    22.0
a    32.0
b     NaN
c    44.0
dtype: float64

---

您可以使用DolphinDB Orca API

import dolphindb.orca as orca
s1=orca.Series([1,2,3,4], index=["a","a","b","c"])
s2=orca.Series([10,20,30,40], index=["a","a","a","c"])
s1+s2
>>> s1+s2
a    11.0
a    21.0
a    31.0
a    12.0
a    22.0
a    32.0
b     NaN
c    44.0
dtype: float64