code: def test_join_multi_levels2(self):
      # some more advanced merges
      # GH6360
      household = DataFrame(
          {
              "household_id": [1, 2, 2, 3, 3, 3, 4],
              "asset_id": [
                  "nl0000301109",
                  "nl0000301109",
                  "gb00b03mlx29",
                  "gb00b03mlx29",
                  "lu0197800237",
                  "nl0000289965",
                  np.nan,
              ],
              "share": [1.0, 0.4, 0.6, 0.15, 0.6, 0.25, 1.0],
          },
          columns=["household_id", "asset_id", "share"],
      ).set_index(["household_id", "asset_id"])
  
      log_return = DataFrame(
          {
              "asset_id": [
                  "gb00b03mlx29",
                  "gb00b03mlx29",
                  "gb00b03mlx29",
                  "lu0197800237",
                  "lu0197800237",
              ],
              "t": [233, 234, 235, 180, 181],
              "log_return": [
                  0.09604978,
                  -0.06524096,
                  0.03532373,
                  0.03025441,
                  0.036997,
              ],
          }
      ).set_index(["asset_id", "t"])
  
      expected = (
          DataFrame(
              {
                  "household_id": [2, 2, 2, 3, 3, 3, 3, 3],
                  "asset_id": [
                      "gb00b03mlx29",
                      "gb00b03mlx29",
                      "gb00b03mlx29",
                      "gb00b03mlx29",
                      "gb00b03mlx29",
                      "gb00b03mlx29",
                      "lu0197800237",
                      "lu0197800237",
                  ],
                  "t": [233, 234, 235, 233, 234, 235, 180, 181],
                  "share": [0.6, 0.6, 0.6, 0.15, 0.15, 0.15, 0.6, 0.6],
                  "log_return": [
                      0.09604978,
                      -0.06524096,
                      0.03532373,
                      0.09604978,
                      -0.06524096,
                      0.03532373,
                      0.03025441,
                      0.036997,
                  ],
              }
          )
          .set_index(["household_id", "asset_id", "t"])
          .reindex(columns=["share", "log_return"])
      )
  
      # this is the equivalency
      result = merge(
          household.reset_index(),
          log_return.reset_index(),
          on=["asset_id"],
          how="inner",
      ).set_index(["household_id", "asset_id", "t"])
      tm.assert_frame_equal(result, expected)
  
      expected = (
          DataFrame(
              {
                  "household_id": [2, 2, 2, 3, 3, 3, 3, 3, 3, 1, 2, 4],
                  "asset_id": [
                      "gb00b03mlx29",
                      "gb00b03mlx29",
                      "gb00b03mlx29",
                      "gb00b03mlx29",
                      "gb00b03mlx29",
                      "gb00b03mlx29",
                      "lu0197800237",
                      "lu0197800237",
                      "nl0000289965",
                      "nl0000301109",
                      "nl0000301109",
                      None,
                  ],
                  "t": [
                      233,
                      234,
                      235,
                      233,
                      234,
                      235,
                      180,
                      181,
                      None,
                      None,
                      None,
                      None,
                  ],
                  "share": [
                      0.6,
                      0.6,
                      0.6,
                      0.15,
                      0.15,
                      0.15,
                      0.6,
                      0.6,
                      0.25,
                      1.0,
                      0.4,
                      1.0,
                  ],
                  "log_return": [
                      0.09604978,
                      -0.06524096,
                      0.03532373,
                      0.09604978,
                      -0.06524096,
                      0.03532373,
                      0.03025441,
                      0.036997,
                      None,
                      None,
                      None,
                      None,
                  ],
              }
          )
          .set_index(["household_id", "asset_id", "t"])
          .reindex(columns=["share", "log_return"])
      )
  
      result = merge(
          household.reset_index(),
          log_return.reset_index(),
          on=["asset_id"],
          how="outer",
      ).set_index(["household_id", "asset_id", "t"])
  
      tm.assert_frame_equal(result, expected)
  
imports: import numpy
  import pytest
  import pandas.util._test_decorators
  import pandas
  from pandas import DataFrame, Index, MultiIndex, RangeIndex, Series, Timestamp, option_context
  import pandas._testing
  from pandas.core.reshape.concat import concat
  from pandas.core.reshape.merge import merge
label_desc: Use image node_id 20 for calling the TestMergeMulti obj's underlying member method code with example usage: obj.test_join_multi_levels2() without return types