how to make an integer index corresponding to a string value?

Question

I'm currently building a recommender system using Goodreads data.

I want to change string user ids into integers. Current user ids are like this: '0d688fe079530ee1fe6fa85eab10ec5c'

I want to change it into integers(e.g. 1, 2, 3, ...), to have the same integer ids which share the same string ids. I've considered using function df.groupby('user_id'), but I couldn't figure out how to do this.

I would be very thankful if anybody let me know how to change.

Answer 1

Use pd.factorize as suggested by @AsishM.

Input data:

                            user_id  book_id  ratings
0  831a1e2505e44a2f81e670db82c9a3c0     1942        3
1  58d3869488a648aebef32b6c2ec4fb16     3116        5
2  f05ad4c0978c4d0eb3ca41921f7a80af     3558        4
3  511c8f47d75c427eae8bead7ff80307b     2467        3
4  db74d6df03644e61b4cd830db35de6a8     2318        2
5  58d3869488a648aebef32b6c2ec4fb16     5882        4
6  db74d6df03644e61b4cd830db35de6a8     6318        5

df['uid'] = pd.factorize(df['user_id'])[0]

Output result:

                            user_id  book_id  ratings  uid
0  831a1e2505e44a2f81e670db82c9a3c0     1942        3    0
1  58d3869488a648aebef32b6c2ec4fb16     3116        5    1  # user 1
2  f05ad4c0978c4d0eb3ca41921f7a80af     3558        4    2
3  511c8f47d75c427eae8bead7ff80307b     2467        3    3
4  db74d6df03644e61b4cd830db35de6a8     2318        2    4  # user 4
5  58d3869488a648aebef32b6c2ec4fb16     5882        4    1  # user 1
6  db74d6df03644e61b4cd830db35de6a8     6318        5    4  # user 4