class_docstr: Pandas ExtensionArray for timedelta data.
  
  .. versionadded:: 0.24.0
  
  .. warning::
  
     TimedeltaArray is currently experimental, and its API may change
     without warning. In particular, :attr:`TimedeltaArray.dtype` is
     expected to change to be an instance of an ``ExtensionDtype``
     subclass.
  
  Parameters
  ----------
  values : array-like
      The timedelta data.
  
  dtype : numpy.dtype
      Currently, only ``numpy.dtype("timedelta64[ns]")`` is accepted.
  freq : Offset, optional
  copy : bool, default False
      Whether to copy the underlying array of data.
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code: def __floordiv__(self, other):
      if isinstance(other, (ABCSeries, ABCDataFrame, ABCIndexClass)):
          return NotImplemented
  
      other = lib.item_from_zerodim(other)
      if is_scalar(other):
          if isinstance(other, (timedelta, np.timedelta64, Tick)):
              other = Timedelta(other)
              if other is NaT:
                  # treat this specifically as timedelta-NaT
                  result = np.empty(self.shape, dtype=np.float64)
                  result.fill(np.nan)
                  return result
  
              # dispatch to Timedelta implementation
              result = other.__rfloordiv__(self._data)
              return result
  
          # at this point we should only have numeric scalars; anything
          #  else will raise
          result = self.asi8 // other
          result[self._isnan] = iNaT
          freq = None
          if self.freq is not None:
              # Note: freq gets division, not floor-division
              freq = self.freq / other
          return type(self)(result.view("m8[ns]"), freq=freq)
  
      if not hasattr(other, "dtype"):
          # list, tuple
          other = np.array(other)
      if len(other) != len(self):
          raise ValueError("Cannot divide with unequal lengths")
  
      elif is_timedelta64_dtype(other):
          other = type(self)(other)
  
          # numpy timedelta64 does not natively support floordiv, so operate
          #  on the i8 values
          result = self.asi8 // other.asi8
          mask = self._isnan | other._isnan
          if mask.any():
              result = result.astype(np.int64)
              result[mask] = np.nan
          return result
  
      elif is_object_dtype(other):
          result = [self[n] // other[n] for n in range(len(self))]
          result = np.array(result)
          if lib.infer_dtype(result, skipna=False) == "timedelta":
              result, _ = sequence_to_td64ns(result)
              return type(self)(result)
          return result
  
      elif is_integer_dtype(other) or is_float_dtype(other):
          result = self._data // other
          return type(self)(result)
  
      else:
          dtype = getattr(other, "dtype", type(other).__name__)
          raise TypeError(
              "Cannot divide {typ} by {cls}".format(
                  typ=dtype, cls=type(self).__name__
              )
          )
  
imports: from __future__ import division
  from datetime import timedelta
  import textwrap
  import warnings
  import numpy
  from pandas._libs import lib, tslibs
  from pandas._libs.tslibs import NaT, Timedelta, Timestamp, iNaT
  from pandas._libs.tslibs.fields import get_timedelta_field
  from pandas._libs.tslibs.timedeltas import array_to_timedelta64, parse_timedelta_unit, precision_from_unit
  import pandas.compat
  from pandas.util._decorators import Appender
  from pandas.core.dtypes.common import _NS_DTYPE, _TD_DTYPE, ensure_int64, is_datetime64_dtype, is_dtype_equal, is_float_dtype, is_integer_dtype, is_list_like, is_object_dtype, is_scalar, is_string_dtype, is_timedelta64_dtype, is_timedelta64_ns_dtype, pandas_dtype
  from pandas.core.dtypes.dtypes import DatetimeTZDtype
  from pandas.core.dtypes.generic import ABCDataFrame, ABCIndexClass, ABCSeries, ABCTimedeltaIndex
  from pandas.core.dtypes.missing import isna
  from pandas.core import ops
  from pandas.core.algorithms import checked_add_with_arr
  import pandas.core.common
  from pandas.tseries.frequencies import to_offset
  from pandas.tseries.offsets import Tick
  from .None import datetimelike
label_desc: Use image node_id 23 for calling the TimedeltaArray obj's underlying member method code with example usage: obj.__floordiv__(other) and returns: NotImplemented, type, result, result, result, result, type, type