I have a simple dataset that I want to do a rolling operation on. The dataset looks like this:

     user_id              create_at             v1
0   15991247    2022-05-31 21:00:21.150822  0.028059
1   24062521    2022-05-31 21:00:33.620000  1.781399
2   12610025    2022-05-31 21:01:30.349000  0.952400
3   24062521    2022-05-31 21:02:38.836000  1.571899
4   24062521    2022-05-31 21:02:44.156000  0.952600

When I attemp to do a rolling operation,

d1 = d1.set_index('create_at')
d1.groupby('user_id')['v1'].rolling('3D').sum().reset_index(drop = True)

I get the correct answer:

0           -0.083971
1           -0.139826
2            1.941623
3            1.169590
4            0.313641
              ...    

But when I attemp to attach it back to the dataset everything becomes NaN, i.e.

d1['roll_3D'] = d1.groupby('user_id')['v1'].rolling('3D').sum().reset_index(drop = True)

                             user_id        v1    roll_3D
create_at           
2022-05-31 21:00:21.150822  15991247    0.028059    NaN
2022-05-31 21:00:33.620000  24062521    1.781399    NaN
2022-05-31 21:01:30.349000  12610025    0.952400    NaN
2022-05-31 21:02:38.836000  24062521    1.571899    NaN
2022-05-31 21:02:44.156000  24062521    0.952600    NaN