Convert Timedelta64[Ns] Column to Seconds in Python Pandas Dataframe

Convert timedelta64[ns] column to seconds in Python Pandas DataFrame

This works properly in the current version of Pandas (version 0.14):

In [132]: df[:5]['duration'] / np.timedelta64(1, 's')
Out[132]: 
0    1232
1    1390
2    1495
3     797
4    1132
Name: duration, dtype: float64

Here is a workaround for older versions of Pandas/NumPy:

In [131]: df[:5]['duration'].values.view('<i8')/10**9
Out[131]: array([1232, 1390, 1495,  797, 1132], dtype=int64)

timedelta64 and datetime64 data are stored internally as 8-byte ints (dtype
'<i8'). So the above views the timedelta64s as 8-byte ints and then does integer
division to convert nanoseconds to seconds.

Note that you need NumPy version 1.7 or newer to work with datetime64/timedelta64s.

Convert pandas timedelta to be displayed in seconds

Use the total_seconds() method on the dt accessor:

foo['DURATION_NEW'].dt.total_seconds()

Convert datetime64 to seconds

Off the top of my head (and with the poor information in the question), if there's a column that contains hours, minutes and seconds, which I will call "time" I would create the following column in the dataframe:

df['full_seconds'] = df['time'].dt.seconds

Or use a simple calculus summing hours, minutes and seconds:

df['full_seconds'] = df['time'].dt.hour * 3600 + df['time'].dt.minute * 60 + df['time'].dt.second

Convert timedelta64[ns] column to seconds in Python Pandas DataFrame

This works properly in the current version of Pandas (version 0.14):

In [132]: df[:5]['duration'] / np.timedelta64(1, 's')
Out[132]: 
0    1232
1    1390
2    1495
3     797
4    1132
Name: duration, dtype: float64

Here is a workaround for older versions of Pandas/NumPy:

In [131]: df[:5]['duration'].values.view('<i8')/10**9
Out[131]: array([1232, 1390, 1495,  797, 1132], dtype=int64)

timedelta64 and datetime64 data are stored internally as 8-byte ints (dtype
'<i8'). So the above views the timedelta64s as 8-byte ints and then does integer
division to convert nanoseconds to seconds.

Note that you need NumPy version 1.7 or newer to work with datetime64/timedelta64s.

How to subtract seconds column from timedelta64 column in pandas?

Try using diff instead:

example_table["x"] = example_table[["Start_Time", "Factor"]].diff(axis=1)['Factor']

Python: Pandas Dataframe How to Convert timedelta column to float column

You can use apply and lambda to access the attribute days (https://pandas.pydata.org/pandas-docs/stable/timedeltas.html):

df_EVENT5_24['ColA'] = df_EVENT5_24.apply(lambda row: row.ColA.days, axis=1)

how to extract days as integers from a timedelta64[ns] object in python

This should convert your timedelta64[ns] type to float64 representing days:

data['difference'].astype('timedelta64[D]')

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