I was working on re-formatting some data in a dataframe and I needed to calculate a value for a new timedelta column which I did by subtracting start date of event with the start date when series is shifted up one row:
data['DURATION_NEW'] = (data['START'] - data['START'].shift(-1)) This work fine and creates a timedelta column, but the data there are in a very strange format:
foo['DURATION_NEW'] Out[80]: 0 -1 days +23:53:30 1 -1 days +15:35:00 2 -1 days +23:50:00 3 -1 days +23:49:00 4 -1 days +23:53:30 1459 -1 days +23:47:00 1461 -1 days +23:51:00 1462 -1 days +22:08:01 1463 -1 days +23:39:30 1464 NaT Name: DURATION_NEW, Length: 1406, dtype: timedelta64[ns] I need to somehow convert this data to be displayed in seconds. First I tried to convert it to a datetime, but for some reason got an error that dtype timedelta64[ns] cannot be converted to datetime64[ns].
Next I tried to manually re-convert it while specifying that I want it to be in seconds:
foo['DURATION_NEW'] = pd.to_timedelta(foo['DURATION_NEW'], unit='sec') That didn't work either. All stays exactly as it is now.
How can I do this properly?
1 Answer
Use the total_seconds() method on the dt accessor:
foo['DURATION_NEW'].dt.total_seconds() 
