code: def test_remove_outliers(outliers_method):
      """Assert that outliers can be removed."""
      data = pycaret.datasets.get_data("juice")
      pc = pycaret.classification.setup(
          data=data,
          low_variance_threshold=None,
          remove_outliers=True,
          outliers_method=outliers_method,
          outliers_threshold=0.2,
      )
      assert pc.pipeline.steps[-1][0] == "remove_outliers"
  
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 34 for calling a global function with example usage: test_remove_outliers(outliers_method) without return types