Lets say I have something that looks like this
df = pd.DataFrame({'Event':['A','A','A','A', 'A' ,'B','B','B','B','B'], 'Number':[1,2,3,4,5,6,7,8,9,10],'Ref':[False,False,False,False,True,False,False,False,True,False]})
What I want to do is create a new column which is the difference in Number from the True in ref. So for the A group, the True is the last one, so the column would read -4,-3,-2,-1,0. I have been thinking to do the following:
for col in df.groupby('Event'):
temp = col[1]
reference = temp[temp.Ref==True]
dist1 = temp.apply(lambda x:x.Number-reference.Number,axis=1)
This seems to correctly calculate for each group, but I am not sure how to join the result into the df.
In your case
df['new']=(df.set_index('Event').Number-df.query('Ref').set_index('Event').Number).to_numpy()
df
Event Number Ref new
0 A 1 False -4
1 A 2 False -3
2 A 3 False -2
3 A 4 False -1
4 A 5 True 0
5 B 6 False -3
6 B 7 False -2
7 B 8 False -1
8 B 9 True 0
9 B 10 False 1
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