code: def test_columns(self):
      # Convert only selected columns. Leave the remaining string columns untouched.
      oe = encoders.OrdinalEncoder(cols=["underscore"])
      result = oe.fit_transform(X)
      self.assertTrue(
          result["underscore"].min() == 1, "should newly be a number"
      )
      self.assertTrue(
          result["unique_str"].min() == "0", "should still be a string"
      )
  
      # If no selection is made, convert all (and only) object columns
      oe = encoders.OrdinalEncoder()
      result = oe.fit_transform(X)
      self.assertTrue(
          result["unique_str"].min() == 1, "should newly be a number"
      )
      self.assertTrue(
          result["invariant"].min() == 1, "should newly be a number"
      )
      self.assertTrue(
          result["underscore"].min() == 1, "should newly be a number"
      )
      self.assertTrue(
          result["none"].min() == 1, "should newly be a number"
      )
      self.assertTrue(
          result["extra"].min() == 1, "should newly be a number"
      )
      self.assertTrue(
          result["categorical"].min() == 1, "should newly be a number"
      )
      self.assertTrue(
          result["na_categorical"].min() == 1,
          "should newly be a number",
      )
      self.assertTrue(
          result["categorical_int"].min() == 1,
          "should newly be a number",
      )
  
      self.assertTrue(
          result["float"].min() < 1,
          "should still be a number and untouched",
      )
      self.assertTrue(
          result["float_edge"].min() < 1,
          "should still be a number and untouched",
      )
      self.assertTrue(
          result["unique_int"].min() < 1,
          "should still be a number and untouched",
      )
  
imports: import warnings
  from datetime import timedelta
  import numpy
  from numpy.testing import assert_array_equal
  import pandas
  import sklearn
  import tests.helpers
  from sklearn.utils.estimator_checks import check_transformer_general, check_transformers_unfitted, check_n_features_in
  from sklearn.compose import ColumnTransformer
  from unittest import TestCase
  from copy import deepcopy
  import category_encoders
label_desc: Use image node_id 43 for calling the TestEncoders obj's underlying member method code with example usage: obj.test_columns() without return types