text: import pandas as pd
  uri = 'https://gist.githubusercontent.com/guilhermesilveira/2d2efa37d66b6c84a722ea627a897ced/raw/10968b997d885cbded1c92938c7a9912ba41c615/tracking.csv'
  data = pd.read_csv(uri)
  data.head()
  
  map = {
      "home" : "tela_inicial",
      "how_it_works" : "nosso_trabalho",
      'contact' : 'contato',
      "bought" : 'comprou'
  }
  data.rename(columns = map)
  
  x = data[['home', 'how_it_works', 'contact']]
  y = data['bought']
  print(data)
  
  data.shape
  
  from sklearn.model_selection import train_test_split
  
  SEED = 24
  
  test = train_test_split(x, y, random_state = SEED, test_size=0.25, stratify=y)
  print(len(test))
  treino_x = test[0]
  teste_x = test[1]
  treino_y = test[2]
  teste_y = test[3]
  
  from sklearn.svm import LinearSVC
  model = LinearSVC()
  model.fit(treino_x, treino_y)
  result = model.predict(teste_x)
  from sklearn.metrics import accuracy_score
  print(f"{accuracy_score(teste_y, result) * 100}%")
  
  print(treino_y.value_counts(), teste_y.value_counts(), sep="\n")