如何将Series列和Dataframe列对齐到同一行

Question

在将pandas系列转换为数据帧后，我尝试将列'Column5'的结果与所有其他列对齐。这是使用下面的代码时的默认行为。我需要这个，因为除了Column5之外，其他列不会被识别为列。我看了一遍，但无法找到帮助：

combinedAllExits = pd.DataFrame(combinedAllExits, columns=['Column5'])

                                                        Column5
Column1                Column2   Column3 Column4          
1 - PAID               201208    8       August         65.0
                       201209    9       September      47.0
                       201210    10      October        54.0
                       201211    11      November       48.0
                       201212    12      December       20.0
                       201301    1       January        64.0
                       201302    2       February       43.0

Answer 1

你需要的IIUC reset_index：

print s
Column1   Column2  Column3  Column4  
1 - PAID  201208   8        August       65.0
          201209   9        September    47.0
          201210   10       October      54.0
          201211   11       November     48.0
          201212   12       December     20.0
          201301   1        January      64.0
          201302   2        February     43.0
Name: Column5, dtype: float64

print s.reset_index()
    Column1  Column2  Column3    Column4  Column5
0  1 - PAID   201208        8     August     65.0
1  1 - PAID   201209        9  September     47.0
2  1 - PAID   201210       10    October     54.0
3  1 - PAID   201211       11   November     48.0
4  1 - PAID   201212       12   December     20.0
5  1 - PAID   201301        1    January     64.0
6  1 - PAID   201302        2   February     43.0

与：

相同

print pd.DataFrame(s, columns=['Column5']).reset_index()
    Column1  Column2  Column3    Column4  Column5
0  1 - PAID   201208        8     August     65.0
1  1 - PAID   201209        9  September     47.0
2  1 - PAID   201210       10    October     54.0
3  1 - PAID   201211       11   November     48.0
4  1 - PAID   201212       12   December     20.0
5  1 - PAID   201301        1    January     64.0
6  1 - PAID   201302        2   February     43.0