pd.to_datetime with multiple format
Use to_datetime with dayfirst=True parameter, for final ouput DD.MM.YYYY HH:MM:SS use Series.dt.strftime:
df = pd.DataFrame({'date':['29.05.2023 01:00:00', 
                           '29.05.2023', 
                           '28.05.2023 23:00:00',
                           '4.10.2023']})


df['date'] = pd.to_datetime(df['date'], dayfirst=True).dt.strftime('%d.%m.%Y %H:%M:%S')
print (df)
                  date
0  29.05.2023 01:00:00
1  29.05.2023 00:00:00
2  28.05.2023 23:00:00
3  04.10.2023 00:00:00


I need to get a timestamp out of multiple time-formats like:
df['date'] = [29.05.2023 01:00:00, 
              29.05.2023, 
              28.05.2023 23:00:00]

At 00:00:00 on every day the time is missing and only the date has been logged.
I need the timestamp to look like this:
df['date'] = [29.05.2023 01:00:00, 
              29.05.2023 00:00:00, 
              28.05.2023 23:00:00]

