Subtract consecutive timeframes in a pandas dataframe given the values of another column

Question

I have a pandas dataframe like this:

    CustomerId        Timestamp         
0.     a         01-09-2018 00:08:00            
1.     a         01-09-2018 00:09:00        
2.     b         01-09-2018 00:11:00        
3.     b         01-09-2018 00:15:00    

I need to calculate the difference in minutes between consecutive timestamps for each customer so that in the end I have something that looks a little like this:

    CustomerId        Timestamp         Difference
0.     a         01-09-2018 00:08:00        -     
1.     a         01-09-2018 00:09:00        1
2.     b         01-09-2018 00:11:00        -
3.     b         01-09-2018 00:15:00        4

I have been trying some loops but nothing seems to be working out. I would really appreciate it if someone could help me out :)

Answer 1

Using groupby with diff

df.groupby('CustomerId').Timestamp.diff().dt.total_seconds()/60
Out[10]: 
0.0    NaN
1.0    1.0
2.0    NaN
3.0    4.0
Name: Timestamp, dtype: float64
df['Different']=df.groupby('CustomerId').Timestamp.diff().dt.total_seconds()/60