text: import matplotlib.pyplot as plt
  from sklearn.metrics import r2_score
  from sklearn.linear_model import LinearRegression
  from sklearn.model_selection import train_test_split
  import pandas as pd
  import numpy as np
  
  
  data_df = pd.read_csv('test.csv')
  data_df.head()
  
  
  x = data_df.drop(['Price'], axis=1).values
  y = data_df['Price'].values
  
  
  x_train, x_test, y_train, y_test = train_test_split(
      x, y, test_size=0.3, random_state=0)
  
  ml = LinearRegression()
  ml.fit(x_train, y_train)
  
  y_pred = ml.predict(x_test)
  print(y_pred)
  
  print(ml.predict([[1, 3.5, 800, 4]]))
  
  print(r2_score(y_test, y_pred))
  
  plt.figure(figsize=(15, 10))
  plt.scatter(y_test, y_pred)
  plt.axis([1000000, 40000000, 1000000, 40000000])
  plt.xlabel('Thực tế')
  plt.ylabel('Dự đoán')
  plt.title('Thực tế và dự đoán')
  plt.show()
  