python - 重组 Pandas 中的数据框

Question

我想重构我的 pandas 数据框，其中 h1、h2 等是与小时相关的值。目前看起来像:

             h1  h2  h3  h4  h5  h6    h7    h8    h9  ...    h15  \
 date                                                              ...          

2004-01-01   46  46  45  41  39  35  33.0  33.0  36.0  ...   55.0   
2004-01-02   43  44  46  46  47  47  47.0  47.0  47.0  ...   54.0   
2004-01-03   45  46  46  44  43  46  46.0  47.0  51.0  ...   69.0   

我想将其重组为如下所示:

    date         value                                                                      

2004-01-01 1:00    46   
2004-01-01 2:00    46     
2004-01-01 3:00    45
2004-01-01 4:00    41 
2004-01-01 5:00    39 
2004-01-01 6:00    35 
2004-01-01 7:00    33
...  
2004-01-02 1:00    43
2004-01-02 2:00    44
2004-01-02 3:00    46  
...       

不确定如何解决这个问题。有什么想法吗？

Answer 1

您可以使用stack然后分配新索引

s=df.stack()
s.index=pd.to_datetime(s.index.get_level_values(level=0)+' '+s.index.get_level_values(level=1).str[1:].str.pad(2,fillchar='0'),format='%Y-%m-%d %H')
s#s.to_frame('Value').reset_index()

Out[1012]: 
2004-01-01 01:00:00    46.0
2004-01-01 02:00:00    46.0
2004-01-01 03:00:00    45.0
2004-01-01 04:00:00    41.0
2004-01-01 05:00:00    39.0
2004-01-01 06:00:00    35.0
2004-01-01 07:00:00    33.0
2004-01-01 08:00:00    33.0
2004-01-01 09:00:00    36.0
2004-01-02 01:00:00    43.0
2004-01-02 02:00:00    44.0
2004-01-02 03:00:00    46.0
2004-01-02 04:00:00    46.0
2004-01-02 05:00:00    47.0
2004-01-02 06:00:00    47.0
2004-01-02 07:00:00    47.0
2004-01-02 08:00:00    47.0
2004-01-02 09:00:00    47.0
2004-01-03 01:00:00    45.0
2004-01-03 02:00:00    46.0
2004-01-03 03:00:00    46.0
2004-01-03 04:00:00    44.0
2004-01-03 05:00:00    43.0
2004-01-03 06:00:00    46.0
2004-01-03 07:00:00    46.0
2004-01-03 08:00:00    47.0
2004-01-03 09:00:00    51.0
dtype: float64