code: def test_causal_manager_global_cohort_effects(self, housing_data):
      train_df, test_df, target_feature = housing_data
  
      manager = CausalManager(
          train_df, test_df, target_feature, ModelTask.REGRESSION, None
      )
      manager.add(["AveRooms"])
      manager.compute()
  
      id = manager.get()[0].id
      X_test = test_df.drop(target_feature, axis=1)
      causal_data = manager.request_global_cohort_effects(id, X_test)
  
      self.verify_common_causal_data_attributes(causal_data)
      assert hasattr(causal_data, "global_effects")
      EFFECTS_ATTRIBUTES = [
          "point",
          "outcome",
          "feature",
          "feature_value",
          "stderr",
          "zstat",
          "ci_lower",
          "ci_upper",
          "p_value",
      ]
      for effect in EFFECTS_ATTRIBUTES:
          assert effect in causal_data.global_effects[0]
  
      incorrect_query_id = "incorrect_query_id"
      X_test = test_df.drop(target_feature, axis=1)
      with pytest.raises(
          ValueError,
          match="Failed to find causal result with ID: "
          "incorrect_query_id",
      ):
          manager.request_global_cohort_effects(
              incorrect_query_id, X_test
          )
  
imports: import os
  from unittest.mock import ANY, patch
  import numpy
  import pytest
  from raiutils.exceptions import UserConfigValidationException
  from raiutils.models import ModelTask
  from responsibleai import RAIInsights
  from responsibleai._interfaces import CausalData
  from responsibleai._internal.constants import FileFormats
  from responsibleai._tools.shared.state_directory_management import DirectoryManager
  from responsibleai.managers.causal_manager import CausalManager
label_desc: Use image node_id 6 for calling the TestCausalManager obj's underlying member method code with example usage: obj.test_causal_manager_global_cohort_effects(housing_data) without return types