code: def to_timedelta(arg, unit="ns", box=True, errors="raise"):
      """
      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, default 'ns'
          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').
      box : bool, default True
          - If True returns a Timedelta/TimedeltaIndex of the results.
          - If False returns a numpy.timedelta64 or numpy.darray of
            values of dtype timedelta64[ns].
      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.
  
      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)
  
      Returning an ndarray by using the 'box' keyword argument:
  
      >>> pd.to_timedelta(np.arange(5), box=False)
      array([0, 1, 2, 3, 4], dtype='timedelta64[ns]')
      """
      unit = parse_timedelta_unit(unit)
  
      if errors not in ("ignore", "raise", "coerce"):
          raise ValueError(
              "errors must be one of 'ignore', " "'raise', or 'coerce'}"
          )
  
      if arg is None:
          return arg
      elif isinstance(arg, ABCSeries):
          from pandas import Series
  
          values = _convert_listlike(
              arg._values, unit=unit, box=False, errors=errors
          )
          return Series(values, index=arg.index, name=arg.name)
      elif isinstance(arg, ABCIndexClass):
          return _convert_listlike(
              arg, unit=unit, box=box, errors=errors, name=arg.name
          )
      elif isinstance(arg, np.ndarray) and arg.ndim == 0:
          # extract array scalar and process below
          arg = arg.item()
      elif is_list_like(arg) and getattr(arg, "ndim", 1) == 1:
          return _convert_listlike(
              arg, unit=unit, box=box, errors=errors
          )
      elif getattr(arg, "ndim", 1) > 1:
          raise TypeError(
              "arg must be a string, timedelta, list, tuple, "
              "1-d array, or Series"
          )
  
      # ...so it must be a scalar value. Return scalar.
      return _coerce_scalar_to_timedelta_type(
          arg, unit=unit, box=box, errors=errors
      )
  
file_path: catboost/contrib/python/pandas/py2/pandas/core/tools/timedeltas.py
imports: import numpy
  from pandas._libs.tslibs.timedeltas import Timedelta, parse_timedelta_unit
  from pandas.core.dtypes.common import is_list_like
  from pandas.core.dtypes.generic import ABCIndexClass, ABCSeries
  import pandas
  from pandas.core.arrays.timedeltas import sequence_to_td64ns
label_desc: Use image node_id 1 for calling a global function with example usage: to_timedelta(arg, unit, box, errors) and returns: _coerce_scalar_to_timedelta_type, arg, Series, _convert_listlike, _convert_listlike