code: def test_transform_feature_to_drop_not_present(df):
      """Test transform when the feature to drop in not in the dataframe."""
      test = DropHighPSIFeatures()
      test.fit(df)
  
      # Define new dataframe with additional column
      data = df.copy()
      data["A"] = [1] * 1000
      # Remove one of the feature to drop
      data = data.drop("drift_1", axis=1)
  
      with pytest.raises(KeyError):
          # Transform
          test.transform(data)
  
imports: from datetime import date
  import math
  import numpy
  import pandas
  import pytest
  from sklearn.datasets import make_classification
  from feature_engine.selection import DropHighPSIFeatures
label_desc: Use image node_id 28 for calling a global function with example usage: test_transform_feature_to_drop_not_present(df) without return types