linear regression using python scipy

linear_regression.py

import numpy
import pylab
from scipy import stats

xi = numpy.arange(0, 9)
A = numpy.array([xi, numpy.ones(9)])
# linearly generated sequence
y = [19, 20, 20.5, 21.5, 22, 23, 23, 25.5, 24]

slope, intercept, r_value, p_value, std_err = stats.linregress(xi, y)

print 'slope', slope
print 'intercept', intercept
print 'r value', r_value
print 'p_value', p_value
print 'standard deviation', std_err

line = slope * xi + intercept
pylab.plot(xi, line, 'r-', xi, y, 'o')
pylab.savefig('fig.png')
pylab.show()
pylab.close()

requirements.txt

numpy
matplotlib
scipy