Identify duplicates and assign similar index in Pandas DataFrame

Suppose that I have a sample data set that can be generated using code below

# Sample DataFrame with duplicate rows
data = {'A': [1, 2, 1, 3, 1, 2, 3, 2],
        'B': [4, 5, 4, 6, 4, 5, 6, 5],
        'C': [1, 2, 3, 4, 5, 6, 7, 8]}
df = pd.DataFrame(data)

In above dataframe I want to assign duplicate rows similar index. For index 0 would be assigned to rows 0, 1 and 4. Similarly index 1 would be assigned to rows 1, 5 and 7. Duplicates should be identified using only column A and B

>Solution :

Use groupby().ngroup:

df.index = df.groupby(['A','B']).ngroup()

Output:

   A  B  C
0  1  4  1
1  2  5  2
0  1  4  3
2  3  6  4
0  1  4  5
1  2  5  6
2  3  6  7
1  2  5  8