old_contents: from unittest import TestCase
  
  import numpy as np
  import pandas as pd
  
  from rosie.chamber_of_deputies.classifiers import ElectionExpensesClassifier
  
  
  class TestElectionExpensesClassifier(TestCase):
  
      def setUp(self):
          self.dataframe = pd.read_csv('rosie/chamber_of_deputies/tests/fixtures/election_expenses_classifier.csv',
                                     dtype={'name': np.str, 'legal_entity': np.str})
          self.election_expenser_classifier = ElectionExpensesClassifier()
  
      def test_is_election_company(self):
          prediction_result = self.election_expenser_classifier.predict(self.dataframe)
  
          self.assertEqual(prediction_result[0], True)
  
      def test_is_not_election_company(self):
          prediction_result = self.election_expenser_classifier.predict(self.dataframe)
  
          self.assertEqual(prediction_result[1], False)
  
      def test_fit_just_for_formality_because_its_never_used(self):
          self.assertTrue(self.election_expenser_classifier.fit(self.dataframe) is None)
  
      def test_transform_just_for_formality_because_its_never_used(self):
          self.assertTrue(self.election_expenser_classifier.transform() is None)
  
new_contents: from unittest import TestCase
  
  import numpy as np
  import pandas as pd
  
  from rosie.chamber_of_deputies.classifiers import ElectionExpensesClassifier
  
  
  class TestElectionExpensesClassifier(TestCase):
  
      def setUp(self):
          self.election_expenser_classifier = ElectionExpensesClassifier()
  
      def test_legal_entity_is_a_election_company(self):
          self.dataframe = pd.read_csv('rosie/chamber_of_deputies/tests/fixtures/election_expenses_classifier.csv',
                                       dtype={'name': np.str, 'legal_entity': np.str})
  
          prediction_result = self.election_expenser_classifier.predict(self.dataframe)
  
          self.assertEqual(prediction_result[0], True)
  
      def test_legal_entity_is_not_election_company(self):
          self.dataframe = pd.read_csv('rosie/chamber_of_deputies/tests/fixtures/election_expenses_classifier.csv',
                                        dtype={'name': np.str, 'legal_entity': np.str})
  
          prediction_result = self.election_expenser_classifier.predict(self.dataframe)
  
          self.assertEqual(prediction_result[1], False)
  
      def test_fit_just_for_formality_because_its_never_used(self):
          empty_dataframe = pd.DataFrame()
          self.assertTrue(self.election_expenser_classifier.fit(empty_dataframe) is None)
  
      def test_transform_just_for_formality_because_its_never_used(self):
          self.assertTrue(self.election_expenser_classifier.transform() is None)
  
subject: refactor test to just read from fixture file when necessary to improve test performance