使用句点选择/切片多索引数据帧时间序列会导致错误？

In[168]: rng = pd.date_range('01-01-2000',periods=50,freq='M') In[169]: long_df = pd.DataFrame(np.random.randn(50,4),index = rng, columns=['bar','baz','foo','zoo']) In[170]: long_df = long_df.stack() In[171]: long_df[:10] Out[171]: 2000-01-31 bar 2.079474 baz -0.569920 foo 1.149012 zoo -0.228926 2000-02-29 bar 0.429502 baz -0.117166 foo 0.956546 zoo -1.483818 2000-03-31 bar -1.137998 baz 1.049849

In[204]: dfmi Out[204]: Last Days to expiry Date Ticker 1988-12-06 HGF89 1.46894 52 HGF90 1.17100 419 HGG89 1.42100 80 HGH89 1.37344 113 HGH90 1.17450 477 HGK89 1.28750 171 HGK90 1.15900 539 HGN89 1.24550 233 HGN90 1.15900 598 HGU89 1.21750 295 HGU90 1.15900 659 HGZ89 1.18500 386 1988-12-07 HGF89 1.51900 51 HGF90 1.18900 418 HGG89 1.46394 79 HGH89 1.41300 112 HGH90 1.19250 476 HGK89 1.31750 170 HGK90 1.17700 538 HGN89 1.27550 232 HGN90 1.17700 597 HGU89 1.24250 294 HGU90 1.17700 658 HGZ89 1.20300 385 1988-12-08 HGF89 1.58100 50 HGF90 1.18900 417 HGG89 1.50894 78 HGH89 1.43994 111 HGH90 1.19250 475 HGK89 1.32750 169 ... ... 2016-07-05 HGK7 2.20500 325 HGM7 2.20900 358 HGN6 2.18150 22 HGN7 2.21000 387 HGQ6 2.18150 55 HGQ7 2.21450 420 HGU6 2.18350 85 HGU7 2.21550 449 HGV6 2.18700 114 HGV7 2.21850 479 HGX6 2.19100 146 HGX7 2.22000 511 HGZ6 2.19250 176 2016-07-06 HGF7 2.16700 205 HGG7 2.17100 233 HGH7 2.17100 266 HGJ7 2.17550 294 HGK7 2.17650 324 HGM7 2.18050 357 HGN6 2.15150 21 HGN7 2.18150 386 HGQ6 2.15150 54 HGQ7 2.18600 419 HGU6 2.15350 84 HGU7 2.18700 448 HGV6 2.15700 113 HGV7 2.19000 478 HGX6 2.16100 145 HGX7 2.19150 510 HGZ6 2.16300 175 [167701 rows x 2 columns] In[204]: dfmi = dfmi.sort_index() In[205]: dfmi.loc['2001'] Out[206]: Last Days to expiry Date Ticker 1988-12-06 HGF89 1.46894 52 HGF90 1.17100 419 HGG89 1.42100 80 HGH89 1.37344 113 HGH90 1.17450 477 HGK89 1.28750 171 HGK90 1.15900 539 HGN89 1.24550 233 HGN90 1.15900 598 HGU89 1.21750 295 HGU90 1.15900 659 1988-12-07 HGF89 1.51900 51 HGF90 1.18900 418 HGG89 1.46394 79 HGH89 1.41300 112 HGH90 1.19250 476 HGK89 1.31750 170 HGK90 1.17700 538 HGN89 1.27550 232 HGN90 1.17700 597 HGU89 1.24250 294 HGU90 1.17700 658 1988-12-08 HGF89 1.58100 50 HGF90 1.18900 417 HGG89 1.50894 78 HGH89 1.43994 111 HGH90 1.19250 475 HGK89 1.32750 169 HGK90 1.17700 537 HGN89 1.27750 231 ... ... 2016-07-05 HGH7 2.19950 267 HGJ7 2.20400 295 HGK7 2.20500 325 HGM7 2.20900 358 HGN6 2.18150 22 HGN7 2.21000 387 HGQ6 2.18150 55 HGQ7 2.21450 420 HGU6 2.18350 85 HGU7 2.21550 449 HGV6 2.18700 114 HGV7 2.21850 479 HGX6 2.19100 146 HGX7 2.22000 511 2016-07-06 HGF7 2.16700 205 HGG7 2.17100 233 HGH7 2.17100 266 HGJ7 2.17550 294 HGK7 2.17650 324 HGM7 2.18050 357 HGN6 2.15150 21 HGN7 2.18150 386 HGQ6 2.15150 54 HGQ7 2.18600 419 HGU6 2.15350 84 HGU7 2.18700 448 HGV6 2.15700 113 HGV7 2.19000 478 HGX6 2.16100 145 HGX7 2.19150 510 [161017 rows x 2 columns]

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1楼 · 发布于 2024-06-23 20:06:51

您需要添加^{}，但需要pandas 0.18.1的最新版本：

print (long_df.loc['2001'])

2001-01-31  bar    1.684425
            baz    1.215258
            foo    0.158968
            zoo    0.689477
2001-02-28  bar   -0.123582
            baz    0.312533
            foo    0.609169
            zoo   -0.093985
2001-03-31  bar    0.372093
            baz   -0.281191
            foo   -0.400354
            zoo    0.646965
2001-04-30  bar   -0.287488
            baz   -0.928941
            foo    1.365416
            zoo    0.267282
2001-05-31  bar   -1.021086
            baz    0.317819
            foo   -0.393135
            zoo   -0.213589
2001-06-30  bar   -2.594173
...
...

编辑：

另一个解决方案是从第一级开始使用^{}查找整数索引的^{}：

^{pr2}$

print (dfmi.iloc[dfmi.index.get_level_values(0).get_loc('2001')])

Date        Ticker                
2001-01-02  HGF01   Last                0.8180
                    Days to expiry     27.0000
            HGF02   Last                0.8180
                    Days to expiry    392.0000
            HGG01   Last                0.8165
                    Days to expiry     55.0000
            HGG02   Last                0.8180
                    Days to expiry    420.0000
            HGH01   Last                0.8115
                    Days to expiry     85.0000
            HGH02   Last                0.8180
                    Days to expiry    448.0000
            HGJ01   Last                0.8125
                    Days to expiry    114.0000
            HGJ02   Last                0.8170
                    Days to expiry    479.0000
            HGK01   Last                0.8135
                    Days to expiry    147.0000
            HGK02   Last                0.8160
                    Days to expiry    512.0000
            HGM01   Last                0.8145
                    Days to expiry    176.0000
            HGM02   Last                0.8155
                    Days to expiry    540.0000
            HGN01   Last                0.8155
                    Days to expiry    206.0000
            HGN02   Last                0.8140
                    Days to expiry    573.0000
            HGQ01   Last                0.8160
                    Days to expiry    239.0000
                                        ...   
2001-12-31  HGK03   Last                0.6960
                    Days to expiry    513.0000
            HGM02   Last                0.6680
                    Days to expiry    177.0000
            HGM03   Last                0.6980
                    Days to expiry    542.0000
            HGN02   Last                0.6710
                    Days to expiry    210.0000
            HGN03   Last                0.7005
                    Days to expiry    575.0000
            HGQ02   Last                0.6740
                    Days to expiry    240.0000
            HGQ03   Last                0.7030
                    Days to expiry    604.0000
            HGU02   Last                0.6770
                    Days to expiry    269.0000
            HGU03   Last                0.7050
                    Days to expiry    634.0000
            HGV02   Last                0.6795
                    Days to expiry    302.0000
            HGV03   Last                0.7080
                    Days to expiry    667.0000
            HGX02   Last                0.6820
                    Days to expiry    329.0000
            HGX03   Last                0.7110
                    Days to expiry    694.0000
            HGZ02   Last                0.6850
                    Days to expiry    361.0000
            HGZ03   Last                0.7140
                    Days to expiry    728.0000
dtype: float64

按注释编辑1：

不幸的是，对于列表理解和^{}如果需要按范围选择，我只有缓慢的解决方案：

print (list(range(1993, 2003)))
[1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002]

dfs = [dfmi.iloc[dfmi.index.get_level_values(0).get_loc(str(x))] for x in range(1993, 2003)]
print (pd.concat(dfs))

1993-01-01 00:00:00  bar    0.080676
                     baz    0.315925
                     foo   -1.484132
                     zoo   -0.977202
1993-01-01 01:00:00  bar    0.817846
                     baz   -1.280649
                     foo    0.727975
                     zoo   -0.062142
1993-01-01 02:00:00  bar    1.278623
                     baz    0.268865
                     foo   -0.183612
                     zoo    0.194996
1993-01-01 03:00:00  bar   -0.304734
                     baz   -0.227468
                     foo   -0.134305
                     zoo    0.887374
1993-01-01 04:00:00  bar   -0.166669
                     baz   -0.132718
                     foo   -0.624932
                     zoo    1.959724
1993-01-01 05:00:00  bar   -1.379774
                     baz   -0.738452
                     foo    0.398924
                     zoo    0.005612
1993-01-01 06:00:00  bar   -0.864205
                     baz   -0.813321
                     foo    0.931858
                     zoo   -1.005977
1993-01-01 07:00:00  bar    0.667380
                     baz   -1.208457
                              ...   
2002-10-30 08:00:00  foo    0.311835
                     zoo    0.611802
2002-10-30 09:00:00  bar    2.615050
                     baz   -0.291767
                     foo   -0.508202
                     zoo    0.443429
2002-10-30 10:00:00  bar   -1.724252
                     baz   -0.126579
                     foo    1.108530
                     zoo   -0.553025
2002-10-30 11:00:00  bar    1.208705
                     baz   -1.561024
                     foo    0.722768
                     zoo    1.893419
2002-10-30 12:00:00  bar    0.239383
                     baz   -0.543053
                     foo   -0.687370
                     zoo    0.848929
2002-10-30 13:00:00  bar    0.897465
                     baz    0.631292
                     foo    0.068200
                     zoo   -1.579010
2002-10-30 14:00:00  bar   -0.996531
                     baz   -1.208318
                     foo    0.174970
                     zoo   -0.780913
2002-10-30 15:00:00  bar    0.237465
                     baz    0.380585
                     foo   -1.646285
                     zoo   -0.730744
dtype: float64

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