numpy.random.shuffle(x) Modify a sequence in-place by shuffling its contents.

RandomState.choice(a, size=None, replace=True, p=None) Generates a random sample from a given 1-D array

RandomState.logseries(p, size=None) Draw samples from a logarithmic series distribution. Samples are

numpy.random.geometric(p, size=None) Draw samples from the geometric distribution. Bernoulli trials are experiments

numpy.random.wald(mean, scale, size=None) Draw samples from a Wald, or inverse Gaussian, distribution. As the scale

RandomState.rayleigh(scale=1.0, size=None) Draw samples from a Rayleigh distribution. The

RandomState.negative_binomial(n, p, size=None) Draw samples from a negative binomial distribution

numpy.random.standard_gamma(shape, size=None) Draw samples from a standard Gamma distribution. Samples are

numpy.random.vonmises(mu, kappa, size=None) Draw samples from a von Mises distribution. Samples are drawn from

RandomState.random_integers(low, high=None, size=None) Random integers of type np.int between low