pandas.to_timedelta

pandas.to_timedelta(arg, unit=None, errors='raise')[source]

Convert argument to timedelta.

Timedeltas are absolute differences in times, expressed in difference units (e.g. days, hours, minutes, seconds). This method converts an argument from a recognized timedelta format / value into a Timedelta type.

Parameters:

arg:str, timedelta, list-like or Series

The data to be converted to timedelta.

Changed in version 2.0: Strings with units ‘M’, ‘Y’ and ‘y’ do not represent unambiguous timedelta values and will raise an exception.

unit:str, optional

Denotes the unit of the arg for numeric arg. Defaults to "ns".

Possible values:

• ‘W’

• ‘D’ / ‘days’ / ‘day’

• ‘hours’ / ‘hour’ / ‘hr’ / ‘h’ / ‘H’

• ‘m’ / ‘minute’ / ‘min’ / ‘minutes’ / ‘T’

• ‘s’ / ‘seconds’ / ‘sec’ / ‘second’ / ‘S’

• ‘ms’ / ‘milliseconds’ / ‘millisecond’ / ‘milli’ / ‘millis’ / ‘L’

• ‘us’ / ‘microseconds’ / ‘microsecond’ / ‘micro’ / ‘micros’ / ‘U’

• ‘ns’ / ‘nanoseconds’ / ‘nano’ / ‘nanos’ / ‘nanosecond’ / ‘N’

Must not be specified when arg contains strings and errors="raise".

Deprecated since version 2.2.0: Units ‘H’, ‘T’, ‘S’, ‘L’, ‘U’ and ‘N’ are deprecated and will be removed in a future version. Please use ‘h’, ‘min’, ‘s’, ‘ms’, ‘us’, and ‘ns’ instead of ‘H’, ‘T’, ‘S’, ‘L’, ‘U’ and ‘N’.

errors:{‘ignore’, ‘raise’, ‘coerce’}, default ‘raise’

• If ‘raise’, then invalid parsing will raise an exception.

• If ‘coerce’, then invalid parsing will be set as NaT.

• If ‘ignore’, then invalid parsing will return the input.

Returns:

timedelta

If parsing succeeded. Return type depends on input:

• list-like: TimedeltaIndex of timedelta64 dtype

• Series: Series of timedelta64 dtype

• scalar: Timedelta

See also

DataFrame.astype

Cast argument to a specified dtype.

to_datetime

Convert argument to datetime.

convert_dtypes

Convert dtypes.

Notes

If the precision is higher than nanoseconds, the precision of the duration is truncated to nanoseconds for string inputs.

Examples

Parsing a single string to a Timedelta:

>>> pd.to_timedelta('1 days 06:05:01.00003')
Timedelta('1 days 06:05:01.000030')
>>> pd.to_timedelta('15.5us')
Timedelta('0 days 00:00:00.000015500')

Parsing a list or array of strings:

>>> pd.to_timedelta(['1 days 06:05:01.00003', '15.5us', 'nan'])
TimedeltaIndex(['1 days 06:05:01.000030', '0 days 00:00:00.000015500', NaT],
               dtype='timedelta64[ns]', freq=None)

Converting numbers by specifying the unit keyword argument:

>>> pd.to_timedelta(np.arange(5), unit='s')
TimedeltaIndex(['0 days 00:00:00', '0 days 00:00:01', '0 days 00:00:02',
                '0 days 00:00:03', '0 days 00:00:04'],
               dtype='timedelta64[ns]', freq=None)
>>> pd.to_timedelta(np.arange(5), unit='d')
TimedeltaIndex(['0 days', '1 days', '2 days', '3 days', '4 days'],
               dtype='timedelta64[ns]', freq=None)