code: import pandas as pd
  import numpy as np
  
  base = pd.read_csv('credit_data.csv')
  base.loc[base.age < 0, 'age'] = 40.92
                 
  previsores = base.iloc[:, 1:4].values
  classe = base.iloc[:, 4].values
  
  from sklearn.impute import SimpleImputer
  imputer = SimpleImputer(missing_values = np.nan, strategy = 'mean')
  imputer = imputer.fit(previsores[:, 1:4])
  previsores[:, 1:4] = imputer.transform(previsores[:, 1:4])
  
  from sklearn.preprocessing import StandardScaler
  scaler = StandardScaler()
  previsores = scaler.fit_transform(previsores)
  
  from sklearn.model_selection import train_test_split
  previsores_treinamento, previsores_teste, classe_treinamento, classe_teste = train_test_split(previsores, classe, test_size=0.25, random_state=0)
  
apis: pandas.read_csv sklearn.impute.SimpleImputer sklearn.model_selection.train_test_split sklearn.preprocessing.StandardScaler