code: def _get_transformer_list(estimators):
      """
      Construct (name, trans, column) tuples from list
  
      """
      transformers, columns = zip(*estimators)
      names, _ = zip(*_name_estimators(transformers))
  
      transformer_list = list(zip(names, transformers, columns))
      return transformer_list
  
imports: from collections import Counter
  from itertools import chain
  from numbers import Integral, Real
  import numpy
  from scipy import sparse
  from ..base import TransformerMixin, _fit_context, clone
  from ..pipeline import _fit_transform_one, _name_estimators, _transform_one
  from ..preprocessing import FunctionTransformer
  from ..utils import Bunch, _get_column_indices, _safe_indexing, check_pandas_support
  from ..utils._estimator_html_repr import _VisualBlock
  from ..utils._param_validation import HasMethods, Hidden, Interval, StrOptions
  from ..utils._set_output import _get_output_config, _safe_set_output
  from ..utils.metaestimators import _BaseComposition
  from ..utils.parallel import Parallel, delayed
  from ..utils.validation import _check_feature_names_in, _num_samples, check_array, check_is_fitted
label_desc: Use image node_id 3 for calling a global function with example usage: _get_transformer_list(estimators) and returns: transformer_list