使用Python中的Pivot函数并排获取两个名称相同的列

Question

我已经使用以下代码创建了表，我不能每次手动重新排列列，因为Ctypes的数量可能会改变。我该怎么做？

from collections import OrderedDict
from pandas import DataFrame
import pandas as pd
import numpy as np
table = OrderedDict((
("Item", ['Item0', 'Item0', 'Item1', 'Item1']),
('CType',['Gold', 'Bronze', 'Gold', 'Silver']),
('USD',  ['1$', '2$', '3$', '4$']),
('EU',   ['1€', '2€', '3€', '4€'])
))
d = DataFrame(table)```
Item    CType   USD EU
0   Item0   Gold    1$  1€
1   Item0   Bronze  2$  2€
2   Item1   Gold    3$  3€
3   Item1   Silver  4$  4€
I am using following code in to rearrange df
p = d.pivot(index='Item', columns='CType')
p.columns = p.columns.map('.'.join)
p = p.reset_index()
Item    USD.Bronze  USD.Gold    USD.Silver  EU.Bronze   EU.Gold EU.Silver
0       Item0       2$          1$          NaN         2€      1€      NaN
1       Item1       NaN         3$          4$          NaN     3€      4€
But I want USD and EU side by side for each CType like below
Item    USD.Bronze EU.Bronze USD.Gold EU.Gold USD.Silver EU.Silver
0       Item0       2$          2€    1$        1€    NaN          NaN
1       Item1       NaN         NaN   3$        3€    4$           4€
I cannot reshuffle columns evertime manually because, the number of Ctypes may change. How can I do this?

Answer 1

通过MultiIndex:添加DataFrame.sort_index

p = (d.pivot(index='Item', columns='CType')
.sort_index(axis=1, level=[1, 0], ascending=[True, False])
.reindex(d['Item'].unique()))
p.columns = p.columns.map('.'.join)
print (p)
USD.Bronze EU.Bronze USD.Gold EU.Gold USD.Silver EU.Silver
Item                                                            
Item0         2$        2€       1$      1€        NaN       NaN
Item1        NaN       NaN       3$      3€         4$        4€