code: def test_pandas_column_name_consistency(estimator):
      _set_checking_parameters(estimator)
      with ignore_warnings(category=(FutureWarning)):
          with warnings.catch_warnings(record=True) as record:
              check_dataframe_column_names_consistency(
                  estimator.__class__.__name__, estimator
              )
          for warning in record:
              assert "was fitted without feature names" not in str(
                  warning.message
              )
  
imports: import warnings
  from collections import OrderedDict
  import numpy
  import pytest
  from sklearn.base import clone
  from sklearn.exceptions import ConvergenceWarning
  from sklearn.utils._testing import SkipTest, ignore_warnings, set_random_state
  from sklearn.utils.estimator_checks import _construct_instance, _get_check_estimator_ids
  from sklearn.utils.estimator_checks import parametrize_with_checks
  from imblearn.over_sampling import RandomOverSampler
  from imblearn.under_sampling import NearMiss, RandomUnderSampler
  from imblearn.utils.estimator_checks import _set_checking_parameters, check_dataframe_column_names_consistency, check_param_validation, parametrize_with_checks
  from imblearn.utils.testing import all_estimators
label_desc: Use image node_id 7 for calling a global function with example usage: test_pandas_column_name_consistency(estimator) without return types