Pandas - Generate Unique ID based on row values

Question

I would like to generate an integer-based unique ID for users (in my df).

Let's say I have:

index  first  last    dob
0      peter  jones   20000101
1      john   doe     19870105
2      adam   smith   19441212
3      john   doe     19870105
4      jenny  fast    19640822

I would like to generate an ID column like so:

index  first  last    dob       id
0      peter  jones   20000101  1244821450
1      john   doe     19870105  1742118427
2      adam   smith   19441212  1841181386
3      john   doe     19870105  1742118427
4      jenny  fast    19640822  1687411973

10 digit ID, but it's based on the value of the fields (john doe identical row values get the same ID).

I've looked into hashing, encrypting, UUID's but can't find much related to this specific non-security use case. It's just about generating an internal identifier.

• I can't use groupby/cat code type methods in case the order of the rows change.
• The dataset won't grow beyond 50k rows.
• Safe to assume there won't be a first, last, dob duplicate.

Feel like I may be tackling this the wrong way as I can't find much literature on it!

Thanks

Answer 1

You can try using hash function.

df['id'] = df[['first', 'last']].sum(axis=1).map(hash)

Please note the hash id is greater than 10 digits and is a unique integer sequence.