Question

我有一个具有行和列多索引的数据框，像这样

Epoch 00011: loss improved from 0.00647 to 0.00646, saving model to ./models_x4/no_noise/dcscn_x2_11.hdf5
1939/1939 - 109s - PSNRLoss: 23.7280 - loss: 0.0065 - SSIMLoss: 0.3329 - val_PSNRLoss: 23.9022 - val_loss: 0.0066 - val_SSIMLoss: 0.3815 - lr: 0.0020
Epoch 12/100

Epoch 00012: loss improved from 0.00646 to 0.00645, saving model to ./models_x4/no_noise/dcscn_x2_12.hdf5
1939/1939 - 111s - PSNRLoss: 23.7245 - loss: 0.0065 - SSIMLoss: 0.3331 - val_PSNRLoss: 23.9397 - val_loss: 0.0066 - val_SSIMLoss: 0.3705 - lr: 0.0020
Epoch 13/100

Epoch 00013: loss improved from 0.00645 to 0.00644, saving model to ./models_x4/no_noise/dcscn_x2_13.hdf5
1939/1939 - 110s - PSNRLoss: 23.7300 - loss: 0.0064 - SSIMLoss: 0.3321 - val_PSNRLoss: 23.9827 - val_loss: 0.0065 - val_SSIMLoss: 0.3745 - lr: 0.0020
Epoch 14/100

Epoch 00014: loss improved from 0.00644 to 0.00643, saving model to ./models_x4/no_noise/dcscn_x2_14.hdf5
1939/1939 - 111s - PSNRLoss: 23.7279 - loss: 0.0064 - SSIMLoss: 0.3376 - val_PSNRLoss: 23.9079 - val_loss: 0.0066 - val_SSIMLoss: 0.3959 - lr: 0.0020
Epoch 15/100

Epoch 00015: loss improved from 0.00643 to 0.00634, saving model to ./models_x4/no_noise/dcscn_x2_15.hdf5
1939/1939 - 110s - PSNRLoss: 23.8356 - loss: 0.0063 - SSIMLoss: 0.3408 - val_PSNRLoss: 23.7063 - val_loss: 0.0067 - val_SSIMLoss: 0.3799 - lr: 0.0010
Epoch 16/100

Epoch 00016: loss did not improve from 0.00634
1939/1939 - 107s - PSNRLoss: 23.8173 - loss: 0.0063 - SSIMLoss: 0.3398 - val_PSNRLoss: 23.7282 - val_loss: 0.0067 - val_SSIMLoss: 0.3853 - lr: 0.0010
Epoch 17/100

Epoch 00017: loss did not improve from 0.00634
1939/1939 - 110s - PSNRLoss: 23.8199 - loss: 0.0063 - SSIMLoss: 0.3426 - val_PSNRLoss: 23.7202 - val_loss: 0.0067 - val_SSIMLoss: 0.4082 - lr: 0.0010
Epoch 18/100

Epoch 00018: loss did not improve from 0.00634
1939/1939 - 110s - PSNRLoss: 23.8138 - loss: 0.0063 - SSIMLoss: 0.3393 - val_PSNRLoss: 23.7523 - val_loss: 0.0066 - val_SSIMLoss: 0.4037 - lr: 0.0010
Epoch 19/100

Epoch 00019: loss improved from 0.00634 to 0.00634, saving model to ./models_x4/no_noise/dcscn_x2_19.hdf5
1939/1939 - 110s - PSNRLoss: 23.8189 - loss: 0.0063 - SSIMLoss: 0.3406 - val_PSNRLoss: 23.7188 - val_loss: 0.0067 - val_SSIMLoss: 0.4115 - lr: 0.0010
Epoch 20/100

Epoch 00020: loss improved from 0.00634 to 0.00634, saving model to ./models_x4/no_noise/dcscn_x2_20.hdf5
1939/1939 - 108s - PSNRLoss: 23.8176 - loss: 0.0063 - SSIMLoss: 0.3407 - val_PSNRLoss: 23.7692 - val_loss: 0.0066 - val_SSIMLoss: 0.3883 - lr: 0.0010
Epoch 21/100

Epoch 00021: loss improved from 0.00634 to 0.00627, saving model to ./models_x4/no_noise/dcscn_x2_21.hdf5
1939/1939 - 108s - PSNRLoss: 23.8889 - loss: 0.0063 - SSIMLoss: 0.3478 - val_PSNRLoss: 24.0306 - val_loss: 0.0064 - val_SSIMLoss: 0.3544 - lr: 5.0000e-04
Epoch 22/100

Epoch 00022: loss improved from 0.00627 to 0.00627, saving model to ./models_x4/no_noise/dcscn_x2_22.hdf5
1939/1939 - 109s - PSNRLoss: 23.8847 - loss: 0.0063 - SSIMLoss: 0.3466 - val_PSNRLoss: 24.0461 - val_loss: 0.0064 - val_SSIMLoss: 0.3679 - lr: 5.0000e-04

我想为此重新编制索引

            BLUB      BLA     
            A    B    C    D
sample
0      blub ...  ...
1      blub ...
2      blub
3      blub
4      blub
0      blub
1      blub
2      blub
...    ...

以不变的方式（复制数据框，而不是就地更改它）。我该如何实现？

Answer 1

由于MultiIndex in index可以通过DataFrame.reset_index和DataFrame.set_index的第一级MultiIndex创建默认索引：

df = (df.reset_index(level=1)
        .reset_index(drop=True)
        .set_index('level_1', append=True)
        .rename_axis(['sample', None]))

或通过MultiIndex.from_arrays：

mux = pd.MultiIndex.from_arrays([np.arange(len(df)), 
                                 df.index.get_level_values(1)], 
                                names=['sample', None])
df = df.set_index(mux)

重新索引数据框多索引

1 个答案: