python - 如何将 Pandas 面板重新索引到 MultiIndex

Question

我有一个 3D 面板数据。我无法将其重新索引为第 2 级的多重索引。

我已经创建了多重索引“mind”。

import pandas as pd

mind = pd.MultiIndex.from_arrays([['Consumer,Cyclical','Industrial','Software'], ['Retail','MiscellaneousManufactur','Technology'], ['AZO','AZZ','AZPN']],names=['sec','sub','ticker'])

dfclose = pd.DataFrame([[1.1,2.1,3.1],[1.2,2.2,3.2]], index=['2013-09-02','2013-09-03'], columns=['AZO','AZZ','AZPN'])
dfmean = dfclose - dfclose.mean()

pdata2 = pd.Panel({'close':dfclose, 'mean':dfmean})
pdata2.minor_axis.name='ticker'
pdata3=pdata2.reindex_axis(mind,axis=2,level='ticker')

但是 pdata3 没有映射到新的多重索引并给出 NaN。

Answer 1

这似乎是 0.12 中的一个错误(将在 0.13 中修复)。
解决方法是不重新索引，而是在创建 dfclose 时使用 MultiIndex:

dfclose = pd.DataFrame([[1.1, 2.1, 3.1], [1.2, 2.2, 3.2]],
                           index=['2013-09-02','2013-09-03'],
                           columns=mind)
dfmean = dfclose - dfclose.mean()
pdata2 = pd.Panel({'close':dfclose, 'mean':dfmean})
pdata2.minor_axis.name='ticker'

In [11]: pdata2.iloc[0]
Out[12]: 
sec         Consumer,Cyclical               Industrial    Software
sub                    Retail  MiscellaneousManufactur  Technology
ticker                    AZO                      AZZ        AZPN
2013-09-02                1.1                      2.1         3.1
2013-09-03                1.2                      2.2         3.2

另一种选择是仅使用 DataFrame:

In [12]: pd.concat([dfmean, dfclose], axis=1, keys=['dfmean' ,'dfclose'])
Out[12]: 
                       dfmean                                                 dfclose                                       
sec         Consumer,Cyclical               Industrial    Software  Consumer,Cyclical               Industrial    Software 
sub                    Retail  MiscellaneousManufactur  Technology             Retail  MiscellaneousManufactur  Technology  
ticker                    AZO                      AZZ        AZPN                AZO                      AZZ        AZPN 
2013-09-02              -0.05                    -0.05       -0.05                1.1                      2.1         3.1  
2013-09-03               0.05                     0.05        0.05                1.2                      2.2         3.2