Bfill on Groupby object

Question

I have a table that looks like this

index	Group	rank	Values
0	a	2	344.0
1	a	3	NaN
2	b	1	455.0
3	a	1	NaN
4	b	2	NaN

I want to group data by 'Group', then sort according to 'rank' and then bfill only for rank == 1. The dataset is very big so I want to avoid loops.

I tried

temp[temp['rank']<=2].sort_values('rank', ascending = True).groupby('Group').bfill(axis='rows', inplace = True)

but this gives me "backfill() got an unexpected keyword argument 'axis'"

user_2901002 · Answer

Remove non exist parameters axis='rows', inplace = True in GroupBy.bfill and assign back to filtered rows:

m = temp['rank']<=2
temp.loc[m, 'Values'] = temp[m].sort_values('rank').groupby('Group')['Values'].bfill()

user_19571156 · Answer

df.sort_values(by = 'rank', inplace = True)

df = df.assign(Values1 = lambda x: x['rank'] == 1).fillna(method = 'bfill')

df.groupby(by = 'Group')['Values']