Q:

split dataframe entries at midnight

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

A:

You can concat the DataFrame of new pairs, then erase the old ones. 
First find the splits:
splits = df[df. End.dt.date > df. Start.dt.date].copy()

Now concatenate and drop:
>>> pd.concat([
    df,
    pd. DataFrame({
        'Start': list(splits. Start) + list(splits. End.dt.floor(freq='1D')),
        'End': list(splits. Start.dt.ceil(freq='1D')) + list(splits. End)})
]).drop(splits.index).sort_values(by='Start')
    End Start
0   2010-02-01 04:00:00 2010-02-01 00:00:00
1   2010-02-01 09:03:00 2010-02-01 05:03:00
2   2010-02-01 14:06:00 2010-02-01 10:06:00
3   2010-02-01 19:09:00 2010-02-01 15:09:00
0   2010-02-02 00:00:00 2010-02-01 20:12:00
2   2010-02-02 00:12:00 2010-02-02 00:00:00
5   2010-02-02 05:15:00 2010-02-02 01:15:00
6   2010-02-02 10:18:00 2010-02-02 06:18:00
7   2010-02-02 15:21:00 2010-02-02 11:21:00
8   2010-02-02 20:24:00 2010-02-02 16:24:00
1   2010-02-03 00:00:00 2010-02-02 21:27:00
3   2010-02-03 01:27:00 2010-02-03 00:00:00

