pandas.
to_timedelta
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.
The data to be converted to timedelta.
Denotes the unit of the arg. Possible values: (‘Y’, ‘M’, ‘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’).
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.
Output type returned if parsing succeeded.
See also
DataFrame.astype
Cast argument to a specified dtype.
to_datetime
Convert argument to datetime.
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 00:00:00.000015')
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 00:00:00.000015', NaT], dtype='timedelta64[ns]', freq=None)
Converting numbers by specifying the unit keyword argument:
>>> pd.to_timedelta(np.arange(5), unit='s') TimedeltaIndex(['00:00:00', '00:00:01', '00:00:02', '00:00:03', '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)