我有一个数据框，grouped具有以下的multiindex列：

import pandas as pd
codes = ["one","two","three"];
colours = ["black", "white"];
textures = ["soft", "hard"];
N= 100 # length of the dataframe
df = pd.DataFrame({ 'id' : range(1,N+1),
                    'weeks_elapsed' : [random.choice(range(1,25)) for i in range(1,N+1)],
                    'code' : [random.choice(codes) for i in range(1,N+1)],
                    'colour': [random.choice(colours) for i in range(1,N+1)],
                    'texture': [random.choice(textures) for i in range(1,N+1)],
                    'size': [random.randint(1,100) for i in range(1,N+1)],
                    'scaled_size': [random.randint(100,1000) for i in range(1,N+1)]
                   },  columns= ['id', 'weeks_elapsed', 'code','colour', 'texture', 'size', 'scaled_size'])
grouped = df.groupby(['code', 'colour']).agg( {'size': [np.sum, np.average, np.size, pd.Series.idxmax],'scaled_size': [np.sum, np.average, np.size, pd.Series.idxmax]}).reset_index()

>> grouped
    code colour     size                           scaled_size                         
                    sum    average  size  idxmax            sum    average  size  idxmax
0    one  black    1031  60.647059    17      81     185.153944  10.891408    17      47
1    one  white     481  37.000000    13      53     204.139249  15.703019    13      53
2  three  black     822  48.352941    17       6     123.269405   7.251141    17      31
3  three  white    1614  57.642857    28      50     285.638337  10.201369    28      37
4    two  black     523  58.111111     9      85      80.908912   8.989879     9      88
5    two  white     669  41.812500    16      78      82.098870   5.131179    16      78
[6 rows x 10 columns]

如何将列索引级别展平/合并为：“ Level1 |
Level2”，例如size|sum，scaled_size|sum。等等？如果这不可能，是否有办法groupby()像我上面所做的那样不创建多索引列？