將多個數據框組合成多索引列的 dataframe

Question

假設我有 3 個數據框，

df_1代表收入

Year        TSLA    MSFT     AVY
2019         851     200   112.8
2018         725     150    92.6

df_2代表其他一些收入

Year        TSLA    MSFT     AVY
2019          10      13      17
2018          11      14      18

df_3代表費用

Year        TSLA    MSFT     AVY
2019         110     213     317
2018         111     214     418

獲取以下df的代碼可能是什么？

       TSLA                             MSFT                             AVY
Year   revenues other_revenues expenses revenues other_revenues expenses revenues other_revenues expenses
2019        851             10      110      200             13      213    112.8             17      317
2018        725             11      111      150             14      214     92.6             18      418

列在哪里是多索引形式？

謝謝

Answer 1

使用concat與DataFrame.swaplevel和DataFrame.sort_index對MultiIndex進行排序：

#if not Year is index first create it
L = [x.set_index('Year') for x in [df_1, df_2, df_3]]
df = (pd.concat(L, 
               axis=1, 
               keys=('evenues', 'other_revenues', 'expenses'))
        .swaplevel(1, 0, axis=1)
        .sort_index(axis=1))
print (df)
         AVY                            MSFT                            TSLA  \
     evenues expenses other_revenues evenues expenses other_revenues evenues   
Year                                                                           
2019   112.8      317             17     200      213             13     851   
2018    92.6      418             18     150      214             14     725   

                              
     expenses other_revenues  
Year                          
2019      110             10  
2018      111             11  

編輯：對於像原始添加DataFrame.reindex通過MultiIndex.from_product從第一級MultiIndex的唯一值的順序：

sub = ['revenues', 'other_revenues', 'expenses']
L = [x.set_index('Year') for x in [df_1, df_2, df_3]]
df = (pd.concat(L, 
               axis=1, 
               keys=sub)
        .swaplevel(1, 0, axis=1))

mux = pd.MultiIndex.from_product([df.columns.levels[0], sub])
df = df.reindex(mux, axis=1)
        
print (df)
         TSLA                             MSFT                          \
     revenues other_revenues expenses revenues other_revenues expenses   
Year                                                                     
2019      851             10      110      200             13      213   
2018      725             11      111      150             14      214   

          AVY                          
     revenues other_revenues expenses  
Year                                   
2019    112.8             17      317  
2018     92.6             18      418