# Random sampling (numpy.random)¶

## Simple random data¶

 rand (d0, d1, ..., dn) Random values in a given shape. randn (d0, d1, ..., dn) Returns zero-mean, unit-variance Gaussian random numbers in an array of shape (d0, d1, ..., dn). randint (low[, high, size]) Return random integers x such that low <= x < high. random_integers (low[, high, size]) Return random integers x such that low <= x <= high. random_sample ([size]) Return random floats in the half-open interval [0.0, 1.0). bytes (length) Return random bytes.

## Permutations¶

 shuffle (x) Modify a sequence in-place by shuffling its contents. permutation (x) Randomly permute a sequence, or return a permuted range.

## Distributions¶

 beta (a, b[, size]) The Beta distribution over [0, 1]. binomial (n, p[, size]) Draw samples from a binomial distribution. chisquare (df[, size]) Draw samples from a chi-square distribution. mtrand.dirichlet (alpha[, size]) Draw samples from the Dirichlet distribution. exponential ([scale, size]) Exponential distribution. f (dfnum, dfden[, size]) Draw samples from a F distribution. gamma (shape[, scale, size]) Draw samples from a Gamma distribution. geometric (p[, size]) Draw samples from the geometric distribution. gumbel ([loc, scale, size]) Gumbel distribution. hypergeometric (ngood, nbad, nsample[, size]) Draw samples from a Hypergeometric distribution. laplace ([loc, scale, size]) Laplace or double exponential distribution. logistic ([loc, scale, size]) Draw samples from a Logistic distribution. lognormal ([mean, sigma, size]) Return samples drawn from a log-normal distribution. logseries (p[, size]) Draw samples from a Logarithmic Series distribution. multinomial (n, pvals[, size]) Draw samples from a multinomial distribution. multivariate_normal (mean, cov[, size]) Draw random samples from a multivariate normal distribution. negative_binomial (n, p[, size]) Negative Binomial distribution. noncentral_chisquare (df, nonc[, size]) Draw samples from a noncentral chi-square distribution. noncentral_f (dfnum, dfden, nonc[, size]) Noncentral F distribution. normal ([loc, scale, size]) Draw random samples from a normal (Gaussian) distribution. pareto (a[, size]) Draw samples from a Pareto distribution with specified shape. poisson ([lam, size]) Poisson distribution. power (a[, size]) Power distribution. rayleigh ([scale, size]) Rayleigh distribution. standard_cauchy ([size]) Standard Cauchy with mode=0. standard_exponential ([size]) Standard exponential distribution (scale=1). standard_gamma (shape[, size]) Standard Gamma distribution. standard_normal ([size]) Standard Normal distribution (mean=0, stdev=1). standard_t (df[, size]) Standard Student’s t distribution with df degrees of freedom. triangular (left, mode, right[, size]) Triangular distribution starting at left, peaking at mode, and ending at right (left <= mode <= right). uniform ([low, high, size]) Draw samples from a uniform distribution. vonmises ([mu, kappa, size]) Draw samples from a von Mises distribution. wald (mean, scale[, size]) Wald (inverse Gaussian) distribution. weibull (a[, size]) Weibull distribution. zipf (a[, size]) Draw samples from a Zipf distribution.

## Random generator¶

 mtrand.RandomState ([seed]) Container for the Mersenne Twister PRNG. seed ([seed]) Seed the generator. get_state () Return a tuple representing the internal state of the generator: set_state (state) Set the state from a tuple.