RandomState.standard_cauchy(size=None) Draw samples from a standard Cauchy distribution with mode =

numpy.random.standard_normal(size=None) Draw samples from a standard Normal distribution (mean=0, stdev=1).

numpy.random.beta(a, b, size=None) Draw samples from a Beta distribution. The Beta distribution is a special case

RandomState.logistic(loc=0.0, scale=1.0, size=None) Draw samples from a logistic distribution. Samples

numpy.random.logistic(loc=0.0, scale=1.0, size=None) Draw samples from a logistic distribution. Samples are drawn

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

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

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

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

RandomState.noncentral_chisquare(df, nonc, size=None) Draw samples from a noncentral chi-square