一个选项是使用pivot_longger from pyjanitor，对于这个特定用例，您传递一个正则表达式列表（到names_pattern），以将所需的列标签聚合到新组中（在names_to中）：

# pip install pyjanitor
import pandas as pd
import janitor

df.pivot_longer(index=None, 
                names_to = ['Buy/Sell', 'Buy/Sell Currency'], 
                names_pattern = [r"Buy$|Sell$", ".+Currency$"], 
                ignore_index = False, 
                sort_by_appearance=True)

            Buy/Sell Buy/Sell Currency
Date                                  
2013-12-31       100               CAD
2013-12-31       100               USD
2014-01-02       200               USD
2014-01-02       200               CAD
2014-01-03       300               CAD
2014-01-03       300               USD
2014-01-06       400               USD
2014-01-06       400               CAD

使用concat

import pandas as pd

print(pd.concat(
    [df['Buy'], df['sell']], axis=1
).stack().reset_index(1, drop=True).rename(index='buy/sell')
)

输出：

0    100
0    100
1    200
1    200
2    300
2    300
3    400
3    400

# assuming that your data has date as index.
df.set_index('date', inplace=True)

# create a mapping to new column names
d={'Buy Currency': 'Buy/Sell Currency', 
   'Sell Currency' : 'Buy/Sell Currency',
   'Buy' : 'Buy/Sell',
   'Sell' :'Buy/Sell'
  }
df.columns=df.columns.map(d)


# stack first two columns over the next two columns
out=pd.concat([ df.iloc[:,:2],
            df.iloc[:,2:]
          ],
           ignore_index=True
          )
out

Buy/Sell    Buy/Sell Currency
0   100     CAD
1   200     USD
2   300     CAD
3   400     USD
4   100     USD
5   200     CAD
6   300     USD
7   400     CAD