How to calculate time-delta between (row 1 and 2) and (row 3 and 4) and so on?

Question

I have the dataset,

ID     Date
1   12/12/2020 13:00
1   12/12/2020 14:00
1   12/12/2020 15:00
1   12/12/2020 16:00
2   12/13/2020 13:00
2   12/13/2020 13:15
2   12/13/2020 14:00
2   12/13/2020 14:30

Expected output,

ID   TimeDelta
1     120mins
2     45mins

I need to find time difference between (row 1 and row 2), (row 3 and row 4) and so on for each GROUPBY and then ADD the difference

Answer 1

One way is to enumerate the rows, then pivot:

enum = df.groupby('ID').cumcount()
df['col'] = enum % 2
df['row'] = enum //2

tmp = df.pivot_table(index=['ID','row'], columns='col', 
                     values='Date', aggfunc='first')
tmp[1].sub(tmp[0]).sum(level=0)

Output:

ID
1   0 days 02:00:00
2   0 days 00:45:00
dtype: timedelta64[ns]