为多索引数据帧的每个索引排序列

Question

我有一个具有多级索引的数据帧。下面是一个片段：

import pandas as pd

data = {'EVENT_ID': [112335580,112335580,112335580,112335580,112335580,112335580,112335580,112335580, 112335582,
                     112335582,112335582,112335582,112335582,112335582,112335582,112335582,112335582,112335582,
                     112335582,112335582,112335582],

 'SELECTION_ID': [6356576,2554439,2503211,6297034,4233251,2522967,5284417,7660920,8112876,7546023,8175276,8145908,
                  8175274,7300754,8065540,8175275,8106158,8086265,2291406,8065533,8125015],

 'BSP': [5.080818565,6.651493872,6.374683435,24.69510797,7.776082305,11.73219964,270.0383021,4,8.294425408,335.3223613,
         14.06040142,2.423340019,126.7205863,70.53780982,21.3328554,225.2711962,92.25113066,193.0151362,3.775394142,
         95.3786641,17.86333041],

  'WIN_LOSE':[1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0]}

df = pd.DataFrame(data, columns=['EVENT_ID', 'SELECTION_ID', 'BSP','WIN_LOSE'])
df

df.set_index(['EVENT_ID', 'SELECTION_ID'], inplace=True)
df.sortlevel(level=0, ascending=True, sort_remaining=True)

我想分别对每个事件ID索引的BSP列进行排序

我尝试了以下方法：

data.assign(BSP=data.groupby(level=0).rank(ascending=False))

这不起作用，因为它会弄乱索引，而且似乎无论如何也不会对列进行排序

我也尝试过按列排序，但这显然也会弄乱索引

Answer 1

这将按BSP升序对每个事件ID进行排序：

df = pd.DataFrame(data, columns=['EVENT_ID', 'SELECTION_ID', 'BSP','WIN_LOSE'])
df = df.sort_values(["EVENT_ID","BSP"])
df.set_index(['EVENT_ID', 'SELECTION_ID'], inplace=True)