text: import numpy as np
  import pytest
  
  from pandas import DataFrame, MultiIndex, Series
  import pandas.util.testing as tm
  
  
  @pytest.fixture
  def simple_multiindex_dataframe():
      """
      Factory function to create simple 3 x 3 dataframe with
      both columns and row MultiIndex using supplied data or
      random data by default.
      """
  
      def _simple_multiindex_dataframe(data=None):
          if data is None:
              data = np.random.randn(3, 3)
          return DataFrame(
              data, columns=[[2, 2, 4], [6, 8, 10]], index=[[4, 4, 8], [8, 10, 12]]
          )
  
      return _simple_multiindex_dataframe
  
  
  @pytest.mark.parametrize(
      "indexer, expected",
      [
          (
              lambda df: df.iloc[0],
              lambda arr: Series(arr[0], index=[[2, 2, 4], [6, 8, 10]], name=(4, 8)),
          ),
          (
              lambda df: df.iloc[2],
              lambda arr: Series(arr[2], index=[[2, 2, 4], [6, 8, 10]], name=(8, 12)),
          ),
          (
              lambda df: df.iloc[:, 2],
              lambda arr: Series(arr[:, 2], index=[[4, 4, 8], [8, 10, 12]], name=(4, 10)),
          ),
      ],
  )
  def test_iloc_returns_series(indexer, expected, simple_multiindex_dataframe):
      arr = np.random.randn(3, 3)
      df = simple_multiindex_dataframe(arr)
      result = indexer(df)
      expected = expected(arr)
      tm.assert_series_equal(result, expected)
  
  
  def test_iloc_returns_dataframe(simple_multiindex_dataframe):
      df = simple_multiindex_dataframe()
      result = df.iloc[[0, 1]]
      expected = df.xs(4, drop_level=False)
      tm.assert_frame_equal(result, expected)
  
  
  def test_iloc_returns_scalar(simple_multiindex_dataframe):
      arr = np.random.randn(3, 3)
      df = simple_multiindex_dataframe(arr)
      result = df.iloc[2, 2]
      expected = arr[2, 2]
      assert result == expected
  
  
  def test_iloc_getitem_multiple_items():
      # GH 5528
      tup = zip(*[["a", "a", "b", "b"], ["x", "y", "x", "y"]])
      index = MultiIndex.from_tuples(tup)
      df = DataFrame(np.random.randn(4, 4), index=index)
      result = df.iloc[[2, 3]]
      expected = df.xs("b", drop_level=False)
      tm.assert_frame_equal(result, expected)
  
  
  def test_iloc_getitem_labels():
      # this is basically regular indexing
      arr = np.random.randn(4, 3)
      df = DataFrame(
          arr,
          columns=[["i", "i", "j"], ["A", "A", "B"]],
          index=[["i", "i", "j", "k"], ["X", "X", "Y", "Y"]],
      )
      result = df.iloc[2, 2]
      expected = arr[2, 2]
      assert result == expected
  
  
  def test_frame_getitem_slice(multiindex_dataframe_random_data):
      df = multiindex_dataframe_random_data
      result = df.iloc[:4]
      expected = df[:4]
      tm.assert_frame_equal(result, expected)
  
  
  def test_frame_setitem_slice(multiindex_dataframe_random_data):
      df = multiindex_dataframe_random_data
      df.iloc[:4] = 0
  
      assert (df.values[:4] == 0).all()
      assert (df.values[4:] != 0).all()
  
  
  def test_indexing_ambiguity_bug_1678():
      # GH 1678
      columns = MultiIndex.from_tuples(
          [("Ohio", "Green"), ("Ohio", "Red"), ("Colorado", "Green")]
      )
      index = MultiIndex.from_tuples([("a", 1), ("a", 2), ("b", 1), ("b", 2)])
  
      df = DataFrame(np.arange(12).reshape((4, 3)), index=index, columns=columns)
  
      result = df.iloc[:, 1]
      expected = df.loc[:, ("Ohio", "Red")]
      tm.assert_series_equal(result, expected)
  
  
  def test_iloc_integer_locations():
      # GH 13797
      data = [
          ["str00", "str01"],
          ["str10", "str11"],
          ["str20", "srt21"],
          ["str30", "str31"],
          ["str40", "str41"],
      ]
  
      index = MultiIndex.from_tuples(
          [("CC", "A"), ("CC", "B"), ("CC", "B"), ("BB", "a"), ("BB", "b")]
      )
  
      expected = DataFrame(data)
      df = DataFrame(data, index=index)
  
      result = DataFrame([[df.iloc[r, c] for c in range(2)] for r in range(5)])
  
      tm.assert_frame_equal(result, expected)
  
  
  @pytest.mark.parametrize(
      "data, indexes, values, expected_k",
      [
          # test without indexer value in first level of MultiIndex
          ([[2, 22, 5], [2, 33, 6]], [0, -1, 1], [2, 3, 1], [7, 10]),
          # test like code sample 1 in the issue
          ([[1, 22, 555], [1, 33, 666]], [0, -1, 1], [200, 300, 100], [755, 1066]),
          # test like code sample 2 in the issue
          ([[1, 3, 7], [2, 4, 8]], [0, -1, 1], [10, 10, 1000], [17, 1018]),
          # test like code sample 3 in the issue
          ([[1, 11, 4], [2, 22, 5], [3, 33, 6]], [0, -1, 1], [4, 7, 10], [8, 15, 13]),
      ],
  )
  def test_iloc_setitem_int_multiindex_series(data, indexes, values, expected_k):
      # GH17148
      df = DataFrame(data=data, columns=["i", "j", "k"])
      df = df.set_index(["i", "j"])
  
      series = df.k.copy()
      for i, v in zip(indexes, values):
          series.iloc[i] += v
  
      df["k"] = expected_k
      expected = df.k
      tm.assert_series_equal(series, expected)
  
  
  def test_getitem_iloc(multiindex_dataframe_random_data):
      df = multiindex_dataframe_random_data
      result = df.iloc[2]
      expected = df.xs(df.index[2])
      tm.assert_series_equal(result, expected)
  