split dataframe entries at midnight

Question

I have a pandas dataframe, with Start and End datatime.

df=pd.DataFrame(data=pd.date_range('20100201', periods=10, freq='5h3min'),columns=['Start'])
df.loc[:,'End']=df.loc[:,'Start']+pd.Timedelta(4,'h')

Start and End can be expected to be sorted interally, but gaps/overlaps may occur between consecutive rows.

I would like to create a new dataframe with the difference that if row contains midnight (e.g. midnight is contained in [Start,End]), the row is then split in two parts before and after midnight ex:

 Start                 End
0 2010-02-01 00:00:00 2010-02-01 04:00:00
1 2010-02-01 05:03:00 2010-02-01 09:03:00
2 2010-02-01 10:06:00 2010-02-01 14:06:00
3 2010-02-01 15:09:00 2010-02-01 19:09:00
4 2010-02-01 20:12:00 2010-02-02 00:12:00
5 2010-02-02 01:15:00 2010-02-02 05:15:00

should be

Start                 End
    0 2010-02-01 00:00:00 2010-02-01 04:00:00
    1 2010-02-01 05:03:00 2010-02-01 09:03:00
    2 2010-02-01 10:06:00 2010-02-01 14:06:00
    3 2010-02-01 15:09:00 2010-02-01 19:09:00
    -----------------------------------------
    4 2010-02-01 20:12:00 2010-02-01 23:59:00
    5 2010-02-02 00:00:00 2010-02-02 00:12:00
    -----------------------------------------
    6 2010-02-02 01:15:00 2010-02-02 05:15:00

Answer 1

I don't believe the above answer works when a midnight time occurs early in the list. Someone correct me if I'm wrong, but I believe anytime you drop the indexes of the "splits" it is then dropping too much from the original list then as well.

I recognize this isn't answering the above question, but I don't have the reputation to comment above. In my case, I believe I will likely just convert to a numpy array, insert rows where the midnight points are, and then copy data accordingly. Ugly, but should work.