The following simple Python code plots the distribution of the produced random numbers using the linear congruential RNG employed by Python. The trend displayed in the previous table is seen rather clearly.
xxxxxxxxxx#!/usr/bin/env pythonimport numpy as npimport matplotlib.mlab as mlabimport matplotlib.pyplot as pltimport random# initialize the rng with a seedrandom.seed() counts = 10000values = np.zeros(counts) for i in range (1, counts, 1): values[i] = random.random()# the histogram of the datan, bins, patches = plt.hist(values, 10, facecolor='green')plt.xlabel('$x$')plt.ylabel('Number of counts')plt.title(r'Test of uniform distribution')plt.axis([0, 1, 0, 1100])plt.grid(True)plt.show()