text: import numpy as np
  import pandas as pd
  import matplotlib.pyplot as plt
  from sklearn.tree import DecisionTreeRegressor
  
  
  dataset = pd.read_csv('position_salaries.csv')
  X = dataset.iloc[:, 1:2].values
  y = dataset.iloc[:, 2].values
  
  regressor = DecisionTreeRegressor(random_state=0)
  regressor.fit(X, y)
  
  y_pred = regressor.predict(6.5)
  
  X_grid = np.arange(min(X), max(X), 0.01)
  X_grid = X_grid.reshape((len(X_grid), 1))
  plt.scatter(X, y, color='red')
  plt.plot(X_grid, regressor.predict(X_grid), color='blue')
  plt.title('Truth or Bluff (Decision Tree Regression)')
  plt.xlabel('Position level')
  plt.ylabel('Salary')
  plt.show()
  