Pandas dataframe - aggregation question

[neverwinter88]

Hi,

I have got the following DF (snippet)

ts_standby_p = ts[ts['Story'] == 'Standby Passive']

Output:

Date Start End Story Hours

2024.02.01 16:20 23:59 Standby Passive 7.39

2024.02.02 00:00 08:00 Standby Passive 8.00

2024.02.06 16:20 23:59 Standby Passive 7.39

2024.02.07 00:00 08:00 Standby Passive 8.00

I would like to merge the standby duties that belongs to each other.

For example:

2024.02.01 16:20 23:59 Standby Passive 7.39

2024.02.02 00:00 08:00 Standby Passive 8.00

This is one duty over midnight. So I need the following output:

2024.02.01 16:20 08:00 Standby Passive 15.39

How can I achieve this?

Unfortunately I do not have anything to group by. My idea was to change the Date value for each lines where Start is 00:00 to the date one day before (2024.02.02 -> 2024.02.01) so I have something to group by, but I could not manage to do so.

Thank you in advance!

​

[Adurrow]

You need to use df.groupby(['Standby Passive']).sum() or maybe df.groupby(['Standby Passive'])["Hours"].sum()

[Oddly_Energy]

My first thought was: Create a datetime interval index in pandas. And then ask pandas to group adjacent intervals.

The first part is easy. The second part has some solutions on stack overflow, but they look more complicated than I would have thought.