text: import pandas as pd
  import matplotlib.pyplot as plt
  import numpy as np
  from sklearn.datasets import make_regression
  
  # the equation 2 * x^3 - 40 * x^2 + 9 * x + 24
  n = 10000
  X = np.random.randn(n)
  randomize = np.random.randint(-500,500, size = n)
  y = []
  for i in range(n):
      y.append((2*X[i]**3)-(40*X[i]**2)+(9*X[i])+24)
  
  for i in range(n):
      y[i] = y[i] + randomize[i]
      
  datadict = {'X': X, 'y': y}
  df = pd.DataFrame(data=datadict)
  df.to_csv('G2.csv')
  plt.scatter(X,y)
  plt.show()
  