Pandas update one df from another based on other columns value

Question

I have two dataframes:

df1:

   A  B  C
0  1  3  5
1  2  4  6

df2:

   A  B   C
0  1  3  50
1  3  5  -1
2  2  4  60

And now I want to update df1 from df2 based on the same values from A and B , to get something like this:

   A  B  C
0  1  3  50
1  2  4  60

What did I try:

• .update() results in A[1] == 3 nad B[1] == 5 , it just goes in order, doesn't match the key (because I cannot specify it there)
• .merge() with left join and on=["A", "B"] - best I got so far, it does preserve the result df to just 2 rows with A=1,2 and B=3,4 , but it adds columns C_x and C_y , the latter with the values I want, but I want them to be in C

Is there a clean way to do this, or should I go for .merge() and just remove the column with _x suffix + rename the C_y to C ?

Answer 1

Drop C in df1 then merge

df1.drop('C', axis=1).merge(df2, on=['A', 'B'], how='left')

   A  B   C
0  1  3  50
1  2  4  60