Python – Updates the pandas data frame with a value equal to the sum of the same df and another df

I have two data frames like this

df1

posting_period      name        sales       profit
    1               client1     50.00       10.00
    1               client2     100.00      20.00
    2               client1     150.00      30.00

df2 (this df does not have the 'profit' column as in df1) 

posting_period      name        sales       
    1               client1     10.00       
    2               client1     20.00   

I want to update client1’s sales in df1 with the sum of client1’s sales in df1

and client1's sales in df2, where posting_periods matches. That is

desired result

posting_period      name        sales       profit
    1               client1     60.00       10.00
    1               client2     100.00      20.00
    2               client1     170.00      30.00

The actual dataframe I’m working with is much larger, but these examples capture what I’m struggling to accomplish. I came up with a very roundabout approach that not only doesn’t work, but it’s not very pythonic. Another challenge is the additional columns in DF1 instead of the additional columns in DF2. I hope someone can come up with an alternative. Thanks!

Start by creating a series that maps index columns from df2 to sales:

idx_cols = ['posting_period', 'name']
s = df2.set_index(idx_cols)['sales']

Then update df1['sales']:: with this series

df1['sales'] += pd. Series(df1.set_index(idx_cols).index.map(s.get)).fillna(0)

Result:

print(df1)

posting_period     name  sales  profit
0               1  client1   60.0    10.0
1               1  client2  100.0    20.0
2               2  client1  170.0    30.0