Create data

actions = ['Start','Action1','Action2','Pause','Actoin3','Resume','Action1','Finish','Start','Action1','Finish']
start_date = datetime.datetime.strptime('14/10/21 09:00:00', '%d/%m/%y %H:%M:%S')
date_list = [start_date   datetime.timedelta(seconds=x) for x in range(0,11)]
values = [1,1,2,1,2,1,5,1,1,1,1]
df = pd.DataFrame({'ActionType': actions,
                   'Timestamp': date_list,
                   'Value': values})

See how there are two "sessions" taking place. I want to mark each session in a new column.

1. How do I get the rows in-between Start and Finish rows? (assume sorted)
2. Similarly, how can I filter-out pauses in the session? For example, to calculate RealTimeElapsed column (or simply make a DuringPause boolean column)

The output should look like this:

output = pd.DataFrame({'Session:': [0,0,0,0,0,0,0,0,1,1,1],
                       'ActionType': actions,
                       'Timestamp': date_list,
                       'RealTimeElapsed': [0,1,2,3,3,3,4,5,0,1,2],
                       'Value': values
                      })

Already considered:

1. Looping: this is a poor practice (my data is very large), but let me know if this is the only feasible solution.
2. Shift: pandas has a shift function, but I only know how to use it for a fixed number of rows, there's no conditional things (e.g. start/finish/pause/resume) I can treat differently
3. Groupby('Type').unstack() and take differences between times: I can't do this because I need to maintain the Value column

CodePudding user response：

My solution is:

df["Session"] = np.where(df["ActionType"]=="Start",1,0).cumsum()-1
df["RealTimeElapsed"] =  df.ActionType.str.contains("Action1|Action2|Pause|Finish").factorize()[0]
df["RealTimeElapsed"] = df.groupby("Session")["RealTimeElapsed"].cumsum()
df = df[["Session","ActionType","Timestamp","RealTimeElapsed","Value"]]
df

returns

    Session ActionType  Timestamp   RealTimeElapsed   Value
   0    0   Start    2021-10-14 09:00:00    0            1
   1    0   Action1  2021-10-14 09:00:01    1            1
   2    0   Action2  2021-10-14 09:00:02    2            2
   3    0   Pause    2021-10-14 09:00:03    3            1
   4    0   Actoin3  2021-10-14 09:00:04    3            2
   5    0   Resume   2021-10-14 09:00:05    3            1
   6    0   Action1  2021-10-14 09:00:06    4            5
   7    0   Finish   2021-10-14 09:00:07    5            1
   8    1   Start    2021-10-14 09:00:08    0            1
   9    1   Action1  2021-10-14 09:00:09    1            1
   10   1   Finish   2021-10-14 09:00:10    2            1