python - how to re rank after drop a row in data in pandas

Question

I have a data result from recommender system like this for example

id          content_id       Rank
08773338    aaaa              1
08773338    bbbb              2
08773338    cccc              3
08333777    bbbb              1
08333777    aaaa              2
08333777    cccc              3

then I want to drop 'bbbb' content id so that it becomes like this

for example

id          content_id       Rank
08773338    aaaa              1
08773338    cccc              3
08333777    aaaa              2
08333777    cccc              3

How do I re-rank the rank column after the bbbb label is removed?

like this

id          content_id       Rank
08773338    aaaa              1
08773338    cccc              2
08333777    aaaa              1
08333777    cccc              2

Answer 1

You can use groupby.rank after masking/subsetting the dataframe:

u = df[df['content_id'].ne("bbbb")].copy()
u['Rank'] = u.groupby("id")['Rank'].rank(method='dense')#.reset_index(drop=True)

---

print(u)
        id content_id  Rank
0  8773338       aaaa   1.0
2  8773338       cccc   2.0
4  8333777       aaaa   1.0
5  8333777       cccc   2.0