class_docstr: pandas-on-Spark MultiIndex that corresponds to pandas MultiIndex logically. This might hold
  Spark Column internally.
  
  Parameters
  ----------
  levels : sequence of arrays
      The unique labels for each level.
  codes : sequence of arrays
      Integers for each level designating which label at each location.
  sortorder : optional int
      Level of sortedness (must be lexicographically sorted by that
      level).
  names : optional sequence of objects
      Names for each of the index levels. (name is accepted for compat).
  copy : bool, default False
      Copy the meta-data.
  verify_integrity : bool, default True
      Check that the levels/codes are consistent and valid.
  
  See Also
  --------
  MultiIndex.from_arrays  : Convert list of arrays to MultiIndex.
  MultiIndex.from_product : Create a MultiIndex from the cartesian product
                            of iterables.
  MultiIndex.from_tuples  : Convert list of tuples to a MultiIndex.
  MultiIndex.from_frame   : Make a MultiIndex from a DataFrame.
  Index : A single-level Index.
  
  Examples
  --------
  >>> ps.DataFrame({'a': ['a', 'b', 'c']}, index=[[1, 2, 3], [4, 5, 6]]).index  # doctest: +SKIP
  MultiIndex([(1, 4),
              (2, 5),
              (3, 6)],
             )
  
  >>> ps.DataFrame({'a': [1, 2, 3]}, index=[list('abc'), list('def')]).index  # doctest: +SKIP
  MultiIndex([('a', 'd'),
              ('b', 'e'),
              ('c', 'f')],
             )
class_docstr_tok: ["pandas-on-Spark","MultiIndex","that","corresponds","to","pandas","MultiIndex","logically",".","This","might","hold","Spark","Column","internally",".","Parameters","--","--","--","--","--","levels",":","sequence","of","arrays","The","unique","labels","for","each","level",".","codes",":","sequence","of","arrays","Integers","for","each","level","designating","which","label","at","each","location",".","sortorder",":","optional","int","Level","of","sortedness","(","must","be","lexicographically","sorted","by","that","level",")",".","names",":","optional","sequence","of","objects","Names","for","each","of","the","index","levels",".","(","name","is","accepted","for","compat",")",".","copy",":","bool",",","default","False","Copy","the","meta-data",".","verify_integrity",":","bool",",","default","True","Check","that","the","levels\/codes","are","consistent","and","valid",".","See","Also","--","--","--","--","MultiIndex.from_arrays",":","Convert","list","of","arrays","to","MultiIndex",".","MultiIndex.from_product",":","Create","a","MultiIndex","from","the","cartesian","product","of","iterables",".","MultiIndex.from_tuples",":","Convert","list","of","tuples","to","a","MultiIndex",".","MultiIndex.from_frame",":","Make","a","MultiIndex","from","a","DataFrame",".","Index",":","A","single-level","Index",".","Examples","--","--","--","--",">",">",">","ps.DataFrame","(","{","'","a","'",":","[","'","a","'",",","'","b","'",",","'","c","'","]","}",",","index=","[","[","1",",","2",",","3","]",",","[","4",",","5",",","6","]","]",")",".index","#","doctest",":","+SKIP","MultiIndex","(","[","(","1",",","4",")",",","(","2",",","5",")",",","(","3",",","6",")","]",",",")",">",">",">","ps.DataFrame","(","{","'","a","'",":","[","1",",","2",",","3","]","}",",","index=","[","list","(","'abc","'",")",",","list","(","'def","'",")","]",")",".index","#","doctest",":","+SKIP","MultiIndex","(","[","(","'","a","'",",","'d","'",")",",","(","'","b","'",",","'","e","'",")",",","(","'","c","'",",","'","f","'",")","]",",",")"]
code: def _is_monotonic_decreasing(self) -> Series:
      window = Window.orderBy(NATURAL_ORDER_COLUMN_NAME).rowsBetween(
          -1, -1
      )
  
      cond = F.lit(True)
      has_not_null = F.lit(True)
      Column = get_column_class()
      for scol in self._internal.index_spark_columns[::-1]:
          data_type = self._internal.spark_type_for(scol)
          prev = F.lag(scol, 1).over(window)
          compare = MultiIndex._comparator_for_monotonic_increasing(
              data_type
          )
          # Since pandas 1.1.4, null value is not allowed at any levels of MultiIndex.
          # Therefore, we should check `has_not_null` over all levels.
          has_not_null = has_not_null & scol.isNotNull()
          cond = F.when(scol.eqNullSafe(prev), cond).otherwise(
              compare(scol, prev, Column.__lt__)
          )
  
      cond = has_not_null & (prev.isNull() | cond)
  
      cond_name = verify_temp_column_name(
          self._internal.spark_frame.select(
              self._internal.index_spark_columns
          ),
          "__is_monotonic_decreasing_cond__",
      )
  
      sdf = self._internal.spark_frame.select(
          self._internal.index_spark_columns + [cond.alias(cond_name)]
      )
  
      internal = InternalFrame(
          spark_frame=sdf,
          index_spark_columns=[
              scol_for(sdf, col)
              for col in self._internal.index_spark_column_names
          ],
          index_names=self._internal.index_names,
          index_fields=self._internal.index_fields,
      )
  
      return first_series(DataFrame(internal))
  
imports: from functools import partial, reduce
  from typing import Any, Callable, Iterator, List, Optional, Tuple, Union, cast, no_type_check
  import pandas
  from pandas.api.types import is_hashable, is_list_like
  from pyspark.sql import functions, Column, Window
  from pyspark.sql.types import DataType
  from pyspark.sql.utils import get_column_class
  from pyspark import pandas
  from pyspark.pandas._typing import Label, Name, Scalar
  from pyspark.pandas.exceptions import PandasNotImplementedError
  from pyspark.pandas.frame import DataFrame
  from pyspark.pandas.indexes.base import Index
  from pyspark.pandas.missing.indexes import MissingPandasLikeMultiIndex
  from pyspark.pandas.series import Series, first_series
  from pyspark.pandas.utils import compare_disallow_null, is_name_like_tuple, name_like_string, scol_for, verify_temp_column_name, validate_index_loc, xor
  from pyspark.pandas.internal import InternalField, InternalFrame, NATURAL_ORDER_COLUMN_NAME, SPARK_INDEX_NAME_FORMAT
label_desc: Use image node_id 22 for calling the MultiIndex obj's underlying member method code with example usage: obj._is_monotonic_decreasing() and returns: first_series