A user is learning python/numpy and wondering if anyone can help with doing a linear regression curve equation in python/numpy?

We can use the following code implement a linear regression curve in Python

import numpy as np

import matplotlib.pyplot as plt

from scipy.optimize import curve_fit

#just some data. Make sure that they are stored in an array, not in a list!!!:

y = np.array([1, 3.8, 7.1, 10.6, 12.6])

x = np.array([0, 1, 2, 3, 4])

#make sure that x is the first argument of linFunc!!

def linFunc(x, k, d):

    return k*x+d

#fitting Algorithm. Cop gives you the 'best' values of k and d, cov is the covariance Matrix.

cop, cov = curve_fit(linFunc, x, y)

xplot = np.linspace(0, 4, 10**4)

plt.figure("data and fitted line")

plt.plot(x, y, 'ro', label = "datapoints")

plt.plot(xplot, linFunc(xplot, *cop), 'b--', label = "fittet function")

plt.xlabel("x-axis")

plt.ylabel("y-axis")

plt.legend()

plt.show()