code: def test_ignore_features():
      """Assert that features can be ignored in preprocessing."""
      data = pycaret.datasets.get_data("juice")
      pc = pycaret.classification.setup(
          data, ignore_features=["Purchase"]
      )
      X, _ = pc.pipeline.transform(pc.X, pc.y)
      assert "Purchase" not in X
  
imports: import io
  import numpy
  import pandas
  import pytest
  from imblearn.over_sampling import ADASYN
  from scipy.sparse import csr_matrix
  from sklearn.decomposition import PCA
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import StandardScaler
  import pycaret.classification
  import pycaret.datasets
  import pycaret.regression
label_desc: Use image node_id 13 for calling a global function with example usage: test_ignore_features() without return types