code: def set_nan_0(train_inputs, holdout_inputs):
      cols = [1, 2, 3, 4, 5]
      train_inputs.iloc[:, cols] = train_inputs.iloc[:, cols].replace(
          0, np.NaN
      )
      holdout_inputs.iloc[:, cols] = holdout_inputs.iloc[
          :, cols
      ].replace(0, np.NaN)
      return train_inputs, holdout_inputs
  
imports: from hyperparameter_hunter import Environment, CVExperiment, FeatureEngineer, EngineerStep
  from hyperparameter_hunter.callbacks.recipes import dataset_recorder
  import numpy
  from numpy.testing import assert_array_almost_equal
  import pandas
  from pandas.testing import assert_frame_equal
  import pytest
  from sklearn.ensemble import AdaBoostClassifier
  from sklearn.preprocessing import StandardScaler
label_desc: Use image node_id 2 for calling a global function with example usage: set_nan_0(train_inputs, holdout_inputs) and returns: train_inputs,  holdout_inputs