code: def test_encoding_categorical_features_duplicate_names():
      """Assert that no duplicate columns are created after OHE"""
      data = pycaret.datasets.get_data("iris")
      data["species_2"] = data["species"].copy()
      data["target"] = data["species"].copy()
      pc = pycaret.classification.setup(data, target="target")
      X, _ = pc.pipeline.transform(pc.X, pc.y)
      assert len(list(X.columns)) == len(set(X.columns))
  
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 27 for calling a global function with example usage: test_encoding_categorical_features_duplicate_names() without return types