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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.
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'
* 'm' / 'minute' / 'min' / 'minutes' / 'T'
* 'S' / 'seconds' / 'sec' / 'second'
* 'ms' / 'milliseconds' / 'millisecond' / 'milli' / 'millis' / 'L'
* 'us' / 'microseconds' / 'microsecond' / 'micro' / 'micros' / 'U'
* 'ns' / 'nanoseconds' / 'nano' / 'nanos' / 'nanosecond' / 'N'
.. versionchanged:: 1.1.0
Must not be specified when `arg` context strings and
``errors="raise"``.
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
-------
timedelta64 or numpy.array of timedelta64
Output type returned if parsing succeeded.
See Also
--------
DataFrame.astype : Cast argument to a specified dtype.
to_datetime : Convert argument to datetime.
convert_dtypes : Convert dtypes.
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)
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