code: def data_X_sf(
      data_sf, request
  ):  # sf is an abbreviation for sensitive features
      X_transform = request.param
      data_sf._replace(X=X_transform(data_sf.X))
      return data_sf
  
imports: from collections import defaultdict, namedtuple
  from test.unit.input_convertors import _map_into_single_column, ensure_dataframe, ensure_list_1d, ensure_ndarray, ensure_ndarray_2d, ensure_series
  import numpy
  import pandas
  import pytest
  from sklearn.base import BaseEstimator, ClassifierMixin
  from fairlearn.postprocessing._constants import LABEL_KEY, SCORE_KEY, SENSITIVE_FEATURE_KEY
  from fairlearn.postprocessing._threshold_operation import ThresholdOperation
label_desc: Use image node_id 4 for calling a global function with example usage: data_X_sf(data_sf, request) and returns: data_sf