Pandas Series: dt.total_seconds() function

Series-dt.total_seconds() function

The dt.total_seconds() function is used to return total duration of each element expressed in seconds.

This method is available directly on TimedeltaArray, TimedeltaIndex and on Series containing timedelta values under the .dt namespace.

Series.dt.total_seconds(self, *args, **kwargs)

Returns: seconds - [ndarray, Float64Index, Series]
When the calling object is a TimedeltaArray, the return type is ndarray. When the calling object is a TimedeltaIndex, the return type is a Float64Index. When the calling object is a Series, the return type is Series of type float64 whose index is the same as the original.

Example - Series:

Python-Pandas Code:

import numpy as np
import pandas as pd

Example - TimedeltaIndex:

Python-Pandas Code:

import numpy as np
import pandas as pd
idx = pd.to_timedelta(np.arange(6), unit='d')
idx

Output:

TimedeltaIndex(['0 days', '1 days', '2 days', '3 days', '4 days', '5 days'], dtype='timedelta64[ns]', freq=None)

Python-Pandas Code:

import numpy as np
import pandas as pd
idx = pd.to_timedelta(np.arange(6), unit='d')
idx.total_seconds()

Output:

Float64Index([0.0, 86400.0, 172800.0, 259200.00000000003, 345600.0, 432000.0], dtype='float64')

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