How to select between conditional statement in pandas dataframe

Question

I have a df that looks like this:

event    response.   duration
0           5          1.1
0           4          0.5
1           5          3.2
0           6          1.2
0           5          2.1
0           5          3.2
1           5          0.9
0           4          1.1
0           4          1.2
0           4          3.1
0           5          0.4
0           5          0.9 

If df.event indicates 1, then the event of interest has occurred. If the event occurred, then I want to see what the response for the next 2 rows. In the next 2 rows, I want to select the response with the greatest duration. I want this information created in a new column, responseType which holds NaN if the event is 0 and the max duration response if event is 1 over the next 2 rows.

It should look like this:

event    response.   duration.  responseType
0           5          1.1         NaN
0           4          0.5         NaN
1           5          3.2         NaN
0           6          2.2         6
0           5          1.1         NaN
0           5          3.2         NaN
1           5          0.9         NaN
0           4          1.1         NaN
0           4          1.2         4
0           4          3.1         NaN
0           5          0.4         NaN
0           5          0.9         NaN

Answer 1

you can use some boolean conditions then assign in a number of ways, here I'll use .idxmax with a .groupby and assign using .loc

con1 = df['event'].eq(1).cumsum()
con2 = df.groupby(df['event'].eq(1).cumsum()).cumcount()
s = df.assign(ky=con1).loc[(con1 > 0) & (con2 <= 2)]
   

---

df.loc[s[s['event'].ne(1)
                   ].groupby('ky')['duration'].idxmax(),'responseType'] = df['response.']


print(df)

    event  response.  duration  responseType
0       0          5       1.1           NaN
1       0          4       0.5           NaN
2       1          5       3.2           NaN
3       0          6       1.2           NaN
4       0          5       2.1           5.0
5       0          5       3.2           NaN
6       1          5       0.9           NaN
7       0          4       1.1           NaN
8       0          4       1.2           4.0
9       0          4       3.1           NaN
10      0          5       0.4           NaN
11      0          5       0.9           NaN

---

print(s)

   event  response.  duration  ky
2      1          5       3.2   1
3      0          6       1.2   1
4      0          5       2.1   1
6      1          5       0.9   2
7      0          4       1.1   2
8      0          4       1.2   2