code: def test_multi_index_unnamed(all_parsers, index_col, columns):
      # see gh-23687
      #
      # When specifying a multi-index header, make sure that
      # we don't error just because one of the rows in our header
      # has ALL column names containing the string "Unnamed". The
      # correct condition to check is whether the row contains
      # ALL columns that did not have names (and instead were given
      # placeholder ones).
      parser = all_parsers
      header = [0, 1]
  
      if index_col is None:
          data = ",".join(columns or ["", ""]) + "\n0,1\n2,3\n4,5\n"
      else:
          data = (
              ",".join([""] + (columns or ["", ""]))
              + "\n,0,1\n0,2,3\n1,4,5\n"
          )
  
      result = parser.read_csv(
          StringIO(data), header=header, index_col=index_col
      )
      exp_columns = []
  
      if columns is None:
          columns = ["", "", ""]
  
      for i, col in enumerate(columns):
          if not col:  # Unnamed.
              col = f"Unnamed: {i if index_col is None else i + 1}_level_0"
  
          exp_columns.append(col)
  
      columns = MultiIndex.from_tuples(zip(exp_columns, ["0", "1"]))
      expected = DataFrame([[2, 3], [4, 5]], columns=columns)
      tm.assert_frame_equal(result, expected)
  
imports: from collections import namedtuple
  from io import StringIO
  import numpy
  import pytest
  from pandas.errors import ParserError
  from pandas import DataFrame, Index, MultiIndex
  import pandas._testing
label_desc: Use image node_id 22 for calling a global function with example usage: test_multi_index_unnamed(all_parsers, index_col, columns) without return types