Pandas:将DataFrameGroupBy对象转换为所需的格式

Question

我有一个数据框如下:

import pandas as pd
import numpy as np
df = pd.DataFrame({'id' : range(1,9),
                   'code' : ['one', 'one', 'two', 'three',
                             'two', 'three', 'one', 'two'],
                   'colour': ['black', 'white','white','white',
                           'black', 'black', 'white', 'white'],
                   'amount' : np.random.randn(8)},  columns= ['id','code','colour','amount'])

我希望能够到组idS按code和colour,然后将它们相对于排序amount.我知道如何groupby():

df.groupby(['code','colour']).head(5)
                id   code colour    amount
code  colour                              
one   black  0   1    one  black -0.117307
      white  1   2    one  white  1.653216
             6   7    one  white  0.817205
three black  5   6  three  black  0.567162
      white  3   4  three  white  0.579074
two   black  4   5    two  black -1.683988
      white  2   3    two  white -0.457722
             7   8    two  white -1.277020

但是,我想要的输出如下所示,其中我有两列:1.code/colour包含键字符串和2. id:amount包含id- amount元组按降序排序wrt amount:

code/colour  id:amount
one/black    {1:-0.117307}
one/white    {2:1.653216, 7:0.817205}
three/black  {6:0.567162}
three/white  {4:0.579074}
two/black    {5:-1.683988}
two/white    {3:-0.457722, 8:-1.277020}

如何DataFrameGroupBy将上面显示的对象转换为我想要的格式？或者,我不应该groupby()首先使用？

编辑: 虽然不是指定的格式,下面的代码给了我我想要的功能:

groups = dict(list(df.groupby(['code','colour'])))
groups['one','white']
   id code colour    amount
1   2  one  white  1.331766
6   7  one  white  0.808739

如何将组减少为仅包括id和amount列？

Answer 1

首先,groupby代码和颜色然后应用自定义函数来格式化id和数量:

df = df.groupby(['code', 'colour']).apply(lambda x:x.set_index('id').to_dict('dict')['amount'])

然后修改索引:

df.index = ['/'.join(i) for i in df.index]

它将返回一个系列,您可以通过以下方式将其转换回DataFrame:

df = df.reset_index()

最后,通过以下方式添加列名:

df.columns=['code/colour','id:amount']

结果:

In [105]: df
Out[105]: 
   code/colour                               id:amount
0    one/black                     {1: 0.392264412544}
1    one/white  {2: 2.13950686015, 7: -0.393002947047}
2  three/black                      {6: -2.0766612539}
3  three/white                     {4: -1.18058561325}
4    two/black                     {5: -1.51959565941}
5    two/white  {8: -1.7659863039, 3: -0.595666853895}