Linrear Regression in Python using Scipy with plot

Here is a linear regression example using the scipy.stats library.

from scipy import stats

import numpy



x = [5.05, 6.75, 3.21, 2.66]

y = [1.65, 26.5, -5.93, 7.96]

plot(x,y,'b+',markersize=19,label='Real Data')



gradient, intercept, r_value, p_value, std_err = stats.linregress(x,y)

print "Gradient and intercept", gradient, intercept



xx= numpy.linspace(-5,10,100)

z=gradient*xx+intercept

plt.plot(xx,z,'r',label='Linear Regression Function')

plt.legend(loc=2)

Here is the result of running the above code: