结合python数据透视表

Question

I would like to have a dataframe, created by combine only the total row values on two pivot tables and keeping the same column names, including the All column.

testA:
             sum                           
        ALL_APPS                           
MONTH        2012/08  2012/09  2012/10  All
DESCRIPTION                                    
A1            111      112      113     336
A2            121      122      123     366
A3            131      132      133     396
All           363      366      369    1098

testA:
             sum                           
        ALL_APPS                           
MONTH        2012/08  2012/09  2012/10  All
DESCRIPTION                                    
A1            211      212      213     636
A2            221      222      223     666
A3            231      232      233     696
All           663      666      669    1998

As I result I would like to have a data frame that would look like:

         2019/08  2019/09  2019/10  All
         363      366      369      1098
         663      666      669      1998

I tried:

A=testA.iloc[3]
B=testB.iloc[3]
my_series = pd.concat([A,B],axis=1)

But it does not do what I expected :(

                         All        All
              MONTH                        
sum ALL_APPS 2019/08  363.0        NaN
             2019/09  366.0        NaN
             2019/10  369.0        NaN
             All      1098.0       NaN
    CUR_VER  2019/08    NaN       663.0
             2019/09    NaN       666.0
             2019/10    NaN       669.0
             All        NaN       1998.0

Answer 1

Try:

my_series=pd.concat([testA.iloc[-1], testB.iloc[-1]], axis=1, ignore_index=True).T

my_series.columns=map(lambda x: x[3], testA.columns)