附加两个熊猫系列到一个数据框的列

Question

我有一个数据帧和两个熊猫系列ac和cc，我想追加这两个系列作为列。但问题是，我的数据框有一个时间指数系列为整数

A='a' 

cc = pd.Series(np.zeros(len(A)*20)) 
ac = pd.Series(np.random.randn(10)) 

我尝试这一点，但我有一个空的数据帧

index = pd.date_range(start=pd.datetime(2017, 1,1), end=pd.datetime(2017, 1, 2), freq='1h') 

df = pd.DataFrame(index=index) 

df = df.join(pd.concat([pd.DataFrame(cc).T] * len(df), ignore_index=True)) 
df = df.join(pd.concat([pd.DataFrame(ac).T] * len(df), ignore_index=True)) 

最终的结果应该是这样的：

    cc ac 
2017-01-01 00:00:00 1 0.247043 
2017-01-01 01:00:00 1 -0.324868 
2017-01-01 02:00:00 1 -0.004868 
2017-01-01 03:00:00 1 0.047043 
2017-01-01 04:00:00 1 -0.447043 
2017-01-01 05:00:00 NaN NaN 
...     ... ... 

如果我们总是在最终结果中有NaN，这不是问题。

---

编辑：

@piRSquared的答案后，我一定要添加一个循环，但我得到了在按键的错误：

az = [cc, ac] 

for i in az: 
    df.join(
      pd.concat(
      [pd.Series(s.values, index[:len(s)]) for s in [i]], 
      axis=1, keys=[i] 
      ) 
     ) 

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all(). 

Answer 1

df.join(
    pd.concat(
     [pd.Series(s.values, index[:len(s)]) for s in [cc, ac]], 
     axis=1, keys=['cc', 'ac'] 
    ) 
) 

         cc  ac 
2017-01-01 00:00:00 0.0 -0.319653 
2017-01-01 01:00:00 0.0 0.630061 
2017-01-01 02:00:00 0.0 -1.648402 
2017-01-01 03:00:00 0.0 -1.141017 
2017-01-01 04:00:00 0.0 -0.643353 
2017-01-01 05:00:00 0.0 0.718771 
2017-01-01 06:00:00 0.0 0.379173 
2017-01-01 07:00:00 0.0 1.799804 
2017-01-01 08:00:00 0.0 0.883260 
2017-01-01 09:00:00 0.0 0.788289 
2017-01-01 10:00:00 0.0  NaN 
2017-01-01 11:00:00 0.0  NaN 
2017-01-01 12:00:00 0.0  NaN 
2017-01-01 13:00:00 0.0  NaN 
2017-01-01 14:00:00 0.0  NaN 
2017-01-01 15:00:00 0.0  NaN 
2017-01-01 16:00:00 0.0  NaN 
2017-01-01 17:00:00 0.0  NaN 
2017-01-01 18:00:00 0.0  NaN 
2017-01-01 19:00:00 0.0  NaN 
2017-01-01 20:00:00 NaN  NaN 
2017-01-01 21:00:00 NaN  NaN 
2017-01-01 22:00:00 NaN  NaN 
2017-01-01 23:00:00 NaN  NaN 
2017-01-02 00:00:00 NaN  NaN