sample python code

sample.py

import numpy as np

def ols(x,y):
    x_mean = x.mean()
    y_mean = y.mean()
    beta_1 = np.multiply((x - x_mean), (y - y_mean)).sum() / np.square((x - x_mean)).sum()
    beta_0 = y_mean - (beta_1 * x_mean)

    def lin_model(new_x, slope=beta_1, intercept=beta_0):
        return new_x * slope + intercept
      
    return lin_model