How to add sequential counter column on groups using Pandas groupby

Question

I feel like there is a better way than this:

import pandas as pd
df = pd.DataFrame(
    [[\'A\', \'X\', 3], [\'A\', \'X\', 5], [\'A\', \'Y\', 7], [\'A\', \'Y         


        

Answer 1

This might be useful

df = df.sort_values(['userID', 'date'])
grp = df.groupby('userID')['ItemID'].aggregate(lambda x: '->'.join(tuple(x))).reset_index()
print(grp)

it will create a sequence like this

Answer 2

use cumcount(), see docs here

In [4]: df.groupby(['c1', 'c2']).cumcount()
Out[4]: 
0     0
1     1
2     0
3     1
4     0
5     1
6     2
7     0
8     0
9     0
10    1
11    2
dtype: int64

If you want orderings starting at 1

In [5]: df.groupby(['c1', 'c2']).cumcount()+1
Out[5]: 
0     1
1     2
2     1
3     2
4     1
5     2
6     3
7     1
8     1
9     1
10    2
11    3
dtype: int64