python - 从宽到长 reshape Pandas 数据框

Question

我正在尝试 reshape 下面的数据框:

        left_id                     right_id                    winner
482393  513d7a69fdc9f03587006808    513ceda3fdc9f035870023db    left
653153  513d5fc2fdc9f03587003c2d    5185d41afdc9f03fd500137c    right
1006476 5140c948fdc9f049260024b4    50f5e76afdc9f065f0007152    right

到

        id                              winner                                              
482393  513d7a69fdc9f03587006808        left
653153  513d5fc2fdc9f03587003c2d        right
1006476 5140c948fdc9f049260024b4        right
482393  513ceda3fdc9f035870023db        left
653153  5185d41afdc9f03fd500137c        right
1006476 50f5e76afdc9f065f0007152        right

我试过 pd.melt(test_cat, id_vars=['left_id', 'right_id'], value_vars=['winner']) 但无法重现我的预期输出。我该怎么做？

示例数据:

pd.DataFrame({'left_id': {482393: '513d7a69fdc9f03587006808',
  653153: '513d5fc2fdc9f03587003c2d',
  1006476: '5140c948fdc9f049260024b4'},
  'right_id': {482393: '513ceda3fdc9f035870023db',
  653153: '5185d41afdc9f03fd500137c',
  1006476: '50f5e76afdc9f065f0007152'},
  'winner': {482393: 'left', 653153: 'right', 1006476: 'right'}}
)

Answer 1

在 melt 中交换参数:

df = pd.melt(test_cat, 
             value_vars=['left_id', 'right_id'], 
             id_vars=['winner'], 
             value_name='id')
print (df)
  winner  variable                        id
0   left   left_id  513d7a69fdc9f03587006808
1  right   left_id  513d5fc2fdc9f03587003c2d
2  right   left_id  5140c948fdc9f049260024b4
3   left  right_id  513ceda3fdc9f035870023db
4  right  right_id  5185d41afdc9f03fd500137c
5  right  right_id  50f5e76afdc9f065f0007152

如果还需要索引值:

df = (pd.melt(test_cat.reset_index(), 
             value_vars=['left_id', 'right_id'], 
             id_vars=['winner', 'index'])
        .set_index('index')
        .rename_axis(None))

print (df)

        winner  variable                     value
482393    left   left_id  513d7a69fdc9f03587006808
653153   right   left_id  513d5fc2fdc9f03587003c2d
1006476  right   left_id  5140c948fdc9f049260024b4
482393    left  right_id  513ceda3fdc9f035870023db
653153   right  right_id  5185d41afdc9f03fd500137c
1006476  right  right_id  50f5e76afdc9f065f0007152

或者使用set_index与 stack :

df = test_cat.set_index('winner', append=True).stack().reset_index([1,2], name='id')
print (df)
        winner   level_2                        id
482393    left   left_id  513d7a69fdc9f03587006808
482393    left  right_id  513ceda3fdc9f035870023db
653153   right   left_id  513d5fc2fdc9f03587003c2d
653153   right  right_id  5185d41afdc9f03fd500137c
1006476  right   left_id  5140c948fdc9f049260024b4
1006476  right  right_id  50f5e76afdc9f065f0007152