Is there a way to append values of a column in a dataframe based on a condition?

Question

I have two datasets, df1 and df2 and would like to create a third column in df2 by appending values in type column of df1 to their corresponding ids in df2. Please note that the ids in df2 can have duplicates and should not be deleted. The dataframes and expected output is as follows:

data1 = [[1283, 234, 8], [1313, 155, 4], 
           [1837, 987,6], [1443, 200, 0],
          [1923, 224, 1], [1912, 247, 7], 
          [1176, 228, 2], [1865, 248, 6], 
          [1219, 265, 3], [1255, 862, 1]] 
      
df1 = pd.DataFrame(data1, columns =['id', 'type', 'qty'])
print(df1)


     id  type  qty
0  1283   234    8
1  1313   155    4
2  1837   987    6
3  1443   200    0
4  1923   224    1
5  1912   247    7
6  1176   228    2
7  1865   248    6
8  1219   265    3
9  1255   862    1

I have another dataframe as follows:

data2 =[[1313, 0], [1313,0], 
      [1443, 0], [1176,0],
      [1912,1], [1912,1], 
      [1912, 1], [1283, 0], 
      [1837, 1], [1837, 1],
      [1837, 1], [1923, 0],
      [1865, 0], [1865, 0],
      [1219, 1], [1255,1]] 
      
df2 = pd.DataFrame(data2, columns =['id', 'class'])
print(df2)


      id    _class
0   1313      0
1   1313      0
2   1443      0
3   1176      0
4   1912      1
5   1912      1
6   1912      1
7   1283      0
8   1837      1
9   1837      1
10  1837      1
11  1923      0
12  1865      0
13  1865      0
14  1219      1
15  1255      1

I would like to append the 'type' value in df1 to their corresponding id to get the following:

      id    _class    type
0   1313      0       155
1   1313      0       155
2   1443      0       200
3   1176      0       228
4   1912      1       247
5   1912      1       247
6   1912      1       247
7   1283      0       234
8   1837      1       987
9   1837      1       987
10  1837      1       987
11  1923      0       224
12  1865      0       248
13  1865      0       248
14  1219      1       265
15  1255      1       862

Answer 1

df2.merge(df1, on="id").drop(["qty"],axis=1)

    id   class  type
0   1313    0   155
1   1313    0   155
2   1443    0   200
3   1176    0   228
4   1912    1   247
5   1912    1   247
6   1912    1   247
7   1283    0   234
8   1837    1   987
9   1837    1   987
10  1837    1   987
11  1923    0   224
12  1865    0   248
13  1865    0   248
14  1219    1   265
15  1255    1   862