import random
import numpy as np
import matplotlib.pyplot as plt

x = []
y = []

for i in range(100):
    x.append(random.uniform(0, 2))
    y.append(4+3*x[i])
    y[i] += np.random.normal(y[i], 1)
    # np.random.normal(loc(mean),scale(STDEV))

plt.plot(x,y,'bo')
# plot x and y using blue circle markers
plt.xlabel("x-axis")
plt.ylabel("y-axis")
plt.title("Y = 4 + 3X + randn with linear regression")

Xb = np.vstack([x, np.ones(len(x))]).T
# Stack arrays in sequence vertically and transpose matrix
b2, b1 = np.linalg.lstsq(Xb, y)[0]
# method of least squares to get fitted line
X = np.array(x)
plt.plot(X, b2*X + b1, 'r')
# red line

plt.show()