Question

需要根据条件向多级数据框中添加列

我需要添加另一列 Bill3 ，这是 bill1＆bill2 的总和注释列为空白

data_frame1 = pd.pivot_table(data_frame, index=['PC', 'Geo', 'Comp'], values=['Bill1', 'Bill2'], columns=['Month'], fill_value=0)
data_frame1 = data_frame1.swaplevel(0,1, axis=1).sort_index(axis=1)
tuples = [(a.strftime('%b-%y'), b) if a!= 'All' else (a,b) for a,b in data_frame1.columns]
data_frame1.columns = pd.MultiIndex.from_tuples(tuples)

输出：

              Sep-19             OCT-19        Nov-19
             Bill1 Bill2      Bill1 Bill2     Bill1 Bill2     
PC Geo Comp
A  Ind   OS   1     1.28        1    1.28      1    1.28

所需的输出：

                 Sep-19                    OCT-19                       Nov-19
             Bill1 Bill2 Bill3 comment   Bill1 Bill2 Bill3 comment   Bill1 Bill2 Bill3  comment  
PC Geo Comp
A  Ind   OS   1     1.28  2.28           1    1.28   2.28             1    1.28   2.28

Answer 1

使用：

#sum all columns
df1 = df.sum(level=0, axis=1)
#sum only bill1, bill2 columns 
#df1 = df.loc[:, df.columns.get_level_values(1).isin(['Bill1','Bill2'])].sum(level=0, axis=1)

#create empty df for comment
df2 = pd.DataFrame(columns=pd.MultiIndex.from_product([df1.columns.tolist(),
                                                      ['comment']]), index=df.index)

#add MultiIndex for bill3
df1.columns = pd.MultiIndex.from_product([df1.columns.tolist(), ['Bill3']])

#join together
df = pd.concat([df, df1, df2], axis=1).sort_index(axis=1)
print (df)
         Nov-19                     Oct-19                     Sep-19        \
          Bill1 Bill2 Bill3 comment  Bill1 Bill2 Bill3 comment  Bill1 Bill2   
A Ind OS      1  1.28  2.28     NaN      1  1.28  2.28     NaN      1  1.28   


         Bill3 comment  
A Ind OS  2.28     NaN

如果订购很重要，请将第一级转换为日期时间：

df.columns = [pd.to_datetime(df.columns.get_level_values(0), format='%b-%y'),
              df.columns.get_level_values(1)]

df1 = df.sum(level=0, axis=1)
df2 = pd.DataFrame(columns=pd.MultiIndex.from_product([df1.columns.tolist(), 
                                            ['comment']]), index=df.index)

df1.columns = pd.MultiIndex.from_product([df1.columns.tolist(), ['Bill3']])

df = pd.concat([df, df1, df2], axis=1).sort_index(axis=1)
print (df)
         2019-09-01                     2019-10-01                      \
              Bill1 Bill2 Bill3 comment      Bill1 Bill2 Bill3 comment   
A Ind OS          1  1.28  2.28     NaN          1  1.28  2.28     NaN   

         2019-11-01                      
              Bill1 Bill2 Bill3 comment  
A Ind OS          1  1.28  2.28     NaN

在多级数据框中添加子列

1 个答案: