Question

我有一个MultiIndex数据帧：

iterables = [['bar', 'baz', 'foo', 'qux'], ['one', 'two']]
Index = pd.MultiIndex.from_product(iterables, names=['first', 'second'])
s  = pd.DataFrame(np.random.randn(8,2), index=Index)

它产生的数据帧如下：

                     0         1
first second                    
bar   one     0.619602 -0.422137
      two    -0.372906  0.581697
baz   one    -0.968921 -0.014957
      two    -0.470649 -1.706410
foo   one     0.834609 -0.600675
      two     0.005306  0.109989
qux   one    -0.713642 -0.173100
      two    -1.155766 -0.365946

现在，在multiIndex的“第二”级别下，我想添加“three”，并使其等于“one”和“two”之间的差异

在下面，A1将等于1.674156 - （ - 1.061293）

A2将等于-1.380391 - （ - 0.620890）

类似的东西：

                     0         1
first second                    
bar   one     1.674156 -1.380391
      two    -1.061293 -0.620890
      three   A1        A2
baz   one     0.839065 -1.985679
      two    -2.086971 -1.415384
      three  
foo   one    -1.673192 -0.559783
      two     0.135445 -1.101833
      three  
qux   one    -0.605042  1.814256
      two     0.182851 -1.819808
      three

我该怎么做？我知道我可以取消堆叠level1，做差异，堆叠回来。只是好奇任何更好的解决方案？

Answer 1

使用stack / unstack / assign

d = s.stack().unstack(1)
d.assign(three=d.one - d.two).stack().unstack(1)

                     0         1
first second                    
bar   one     0.877453  0.214777
      two    -0.741437  0.185339
      three   1.618890  0.029437
baz   one     1.358314 -0.315129
      two     1.881061  0.253034
      three  -0.522747 -0.568162
foo   one     1.663033 -0.879386
      two    -0.658539 -0.331162
      three   2.321572 -0.548224
qux   one    -0.171216 -0.510144
      two     0.855199 -0.653881
      three  -1.026415  0.143737

将级别添加到multiIndex数据帧

1 个答案: