Add column to dataframe based on corresponding values of two row values from another dataframe

user_13487249 0
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I have two data frames:

df1 = pd.DataFrame({'X1':[2,2,2,2,3,3,3,3,4,4,4,5,5,5,5], 
                'X2':[10,20,70,80,10,20,70,80,50,70,80,60,70,80,90], 
                'X3':[0,1,0,1,1,1,1,0,0,0,1,1,0,0,0]})


     X1  X2  X3
0    2  10   0
1    2  20   1
2    2  70   0
3    2  80   1
4    3  10   1
5    3  20   1
6    3  70   1
7    3  80   0
8    4  50   0
9    4  70   0
10   4  80   1
11   5  60   1
12   5  70   0
13   5  80   0
14   5  90   0

and the other one is df2:

df2 = pd.DataFrame({'X1':[2,3,3,4,5,5,5], 
                'X2':[10,20,70,50,60,70,80]})

   X1  X2
0   2  10
1   3  20
2   3  70
3   4  50
4   5  60
5   5  70
6   5  80

I need to find the corresponding X3 values for df2 based on the value of X1 and X2 in each row of df1.The results should be something like the following:

    X1  X2  X3
0   2  10   0
1   3  20   1
2   3  70   1
3   4  50   0
4   5  60   1
5   5  70   0
6   5  80   0
pandas dataframe
2 Answers

Use pandas.DataFrame.merge:

df3 = df2.merge(df1, on=["X1", "X2"])
print(df3)

Output:

   X1  X2  X3
0   2  10   0
1   3  20   1
2   3  70   1
3   4  50   0
4   5  60   1
5   5  70   0
6   5  80   0
user_70937410 
df2 = df2.join(df1.set_index(['X1', 'X2']), on=['X1', 'X2'])

# display(df2)
   X1  X2  X3
0   2  10   0
1   3  20   1
2   3  70   1
3   4  50   0
4   5  60   1
5   5  70   0
6   5  80   0
user_77588040
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