Sum specific dataframe rows by columns

Question

I have a multi index dataframe (df):

working_pattern    Full-time       Part-time    
sex             Male  Female    Male  Female
salary_band             
  Up to 15000    630     208     403     348
15001 - 20000    741     279     170     401
20001 - 25000    929     722     320     596
25001 - 30000    818     571     725     587
30001 - 35000    175     273     711     383
35001 - 40000    212     928     855     929
40001 - 45000    586     937     577     141
45001 - 50000    876     382     995     786

I am trying to sum rows 40001 - 45000 and 45001 - 50000 . So the output looks like:

working_pattern  Full-time     Part-time    
sex           Male  Female  Male  Female
salary_band             
  Up to 15000  630     208   403     348
15001 - 20000  741     279   170     401
20001 - 25000  929     722   320     596
25001 - 30000  818     571   725     587
30001 - 35000  175     273   711     383
35001 - 40000  212     928   855     929
      40001 + 1462    1319  1572     927

I have tried:

df["40001 +"]  = df.loc[['40001 - 45000','45001 - 50000']].sum()

without success

Answer 1

Use DataFrame.loc for add new row:

df.loc["40001 +"]  = df.loc[['40001 - 45000','45001 - 50000']].sum()
print (df)
working_pattern Full-time        Part-time       
sex                  Male Female      Male Female
salary_band                                      
Up to 15000           630    208       403    348
15001 - 20000         741    279       170    401
20001 - 25000         929    722       320    596
25001 - 30000         818    571       725    587
30001 - 35000         175    273       711    383
35001 - 40000         212    928       855    929
40001 - 45000         586    937       577    141
45001 - 50000         876    382       995    786
40001 +              1462   1319      1572    927