docstr: Test that the mean is correctly computed on unbalanced groups
docstr_tok: ["Test","that","the","mean","is","correctly","computed","on","unbalanced","groups"]
code: def test_unbalanced_groups(self):
      """Test that the mean is correctly computed on unbalanced groups"""
      data = pd.DataFrame(
          data={
              "id": [0, 0, 0, 0, 1, 1, 1, 2, 2],
              "order": [0, 1, 2, 3, 0, 1, 2, 0, 1],
              "best": [0.1, 0.7, 0.6, 0.5, 0.4, 0.2, 0.5, 0.3, 0.1],
          }
      )
  
      result = ranking(data)
  
      assert result["rank"].tolist() == [0, 2, 1, 0, 2, 1, 0, 1, 0]
  
imports: import numpy
  import pandas
  import pytest
  from sklearn.ensemble import AdaBoostRegressor, BaggingRegressor, ExtraTreesRegressor, GradientBoostingRegressor, RandomForestRegressor
  from orion.analysis.base import average, flatten_numpy, flatten_params, ranking, to_numpy, train_regressor
  from orion.core.io.space_builder import SpaceBuilder
  from orion.core.worker.transformer import build_required_space
label_desc: Use image node_id 4 for calling the TestRanking obj's underlying member method code with example usage: obj.test_unbalanced_groups() without return types