code: def _get_objs_combined_axis(objs, intersect=False, axis=0, sort=True):
      """
      Extract combined index: return intersection or union (depending on the
      value of "intersect") of indexes on given axis, or None if all objects
      lack indexes (e.g. they are numpy arrays).
  
      Parameters
      ----------
      objs : list of objects
          Each object will only be considered if it has a _get_axis
          attribute.
      intersect : bool, default False
          If True, calculate the intersection between indexes. Otherwise,
          calculate the union.
      axis : {0 or 'index', 1 or 'outer'}, default 0
          The axis to extract indexes from.
      sort : bool, default True
          Whether the result index should come out sorted or not.
  
      Returns
      -------
      Index
      """
      obs_idxes = [
          obj._get_axis(axis)
          for obj in objs
          if hasattr(obj, "_get_axis")
      ]
      if obs_idxes:
          return _get_combined_index(
              obs_idxes, intersect=intersect, sort=sort
          )
  
imports: import textwrap
  import warnings
  from pandas._libs import NaT, lib
  import pandas.core.common
  from pandas.core.indexes.base import Index, _new_Index, ensure_index, ensure_index_from_sequences
  from pandas.core.indexes.base import InvalidIndexError
  from pandas.core.indexes.category import CategoricalIndex
  from pandas.core.indexes.datetimes import DatetimeIndex
  from pandas.core.indexes.interval import IntervalIndex
  from pandas.core.indexes.multi import MultiIndex
  from pandas.core.indexes.numeric import Float64Index, Int64Index, NumericIndex, UInt64Index
  from pandas.core.indexes.period import PeriodIndex
  from pandas.core.indexes.range import RangeIndex
  from pandas.core.indexes.timedeltas import TimedeltaIndex
label_desc: Use image node_id 1 for calling a global function with example usage: _get_objs_combined_axis(objs, intersect, axis, sort) and returns: _get_combined_index