我有一个csv文件，我将其读入熊猫框架：
import pandas as pd
csv_file = pd.read_csv('hello.csv', engine='c', delimiter=',', index_col=0,
skiprows=1, header=[0, 1])
这是csv文件（print（csv_file））的视图：
bodyparts nose ... right_ear
coords x y ... y likelihood
0 197.486369 4.545954 ... 206.351233 1.280000e-06
1 319.946460 191.035224 ... 206.321893 9.680000e-07
2 319.880388 191.012984 ... 206.322207 9.520000e-07
3 320.286005 190.843329 ... 206.227396 1.020000e-06
4 320.210989 190.863304 ... 3.106570 8.350000e-07
5 320.212529 190.867178 ... 3.116692 8.460000e-07
6 -0.794705 2.462400 ... 3.112797 8.500000e-07
7 -0.785404 2.485562 ... 3.117945 8.430000e-07
8 319.786777 191.003882 ... 3.125062 8.820000e-07
9 319.947064 191.030201 ... 206.202980 9.210000e-07
10 319.845807 191.002510 ... 206.177779 8.660000e-07
11 320.135816 190.967408 ... 206.190732 8.910000e-07
12 -0.935765 2.568168 ... 206.260773 8.860000e-07
13 -0.932833 2.525062 ... 206.273504 8.780000e-07
14 -0.960939 2.500079 ... 206.272811 8.680000e-07
15 -0.832561 2.442907 ... 206.266416 8.720000e-07
16 -0.838884 2.421689 ... 206.242941 9.440000e-07
17 -0.857173 2.421467 ... 206.243972 9.950000e-07
18 -0.841627 2.414854 ... 206.225004 9.820000e-07
... ... ... ... ... ...
10459 349.556703 301.995042 ... 307.018688 9.999745e-01
10460 348.608277 301.098244 ... 309.648986 9.999962e-01
10461 349.995217 303.397438 ... 311.149967 9.999974e-01
10462 349.109666 305.710711 ... 311.893106 9.999955e-01
10463 352.142571 310.081763 ... 317.420410 9.907742e-01
10464 351.916488 317.078128 ... 319.407211 2.706501e-01
10465 353.809847 320.086683 ... 323.478481 9.911720e-01
10466 349.233529 321.859424 ... 323.383276 8.724346e-01
生成的数据帧具有两个级别的MultiIndexed：
tuple(('body_part1', 'body_part2', ..., 'body_partn'), ('x', 'y', 'likelihood')
我想对“ y”键下的每一行应用一个函数，并使用该函数的输出重新打包数据框。我该怎么做？
功能用途：该功能是使用y_max值对y值进行归一化和/或反转。
侧面问题
为什么这样做：
csv_file.groupby('y', axis=1, level=1)
返回：
KeyError: 'y'