I am a self taught coder (for around a year, so new). Here is my data
phData = pd.read_excel('phone call log & duration.xlsx')
called from called to Date Time Duration in (sec)
0 7722078014 7722012013 2017-07-01 10:00:00 303
1 7722078014 7722052018 2017-07-01 10:21:00 502
2 7722078014 7450120521 2017-07-01 10:23:00 56
The dtypes are:
called from int64
called to int64
Date datetime64[ns]
Time object
Duration in (sec) int64
dtype: object
phData['Time'] = pd.to_datetime(phData['Time'], format='%H:%M:%S')
phData.head(2)
called from called to Date Time Duration in (sec)
0 7722078014 7722012013 2017-07-01 1900-01-01 10:00:00 303
1 7722078014 7722052018 2017-07-01 1900-01-01 10:21:00 502
I've managed to change the 'Time' to datetime64[ns] but somehow dates have been added?? From where I have no idea? I want to be able to analyse the Date and Time using Pandas which I'm happy to do. To explore calls made between dates and time, frequency etc. I think also I will be able to save it so it will work in Orange3. But Orange3 won't recognise the Time as a time format. I've tried stripping out the 1900-01-01 but get an error saying it can only be done if an object. I think the Time isn't a datetime but a datetime.time ??? and I'm not sure why this matters and how to simply have 2 columns one Date and another Time, that Pandas will recognise for me to mine. I have looked at countless posts and that's where I found how to use pd.to_datetime and that my issue might be datetime.time but I'm stuck after this.