np.random

Simple random data

choice(a[, size, replace, p, device, out])

Generates a random sample from a given 1-D array

Permutations

shuffle(x)

Modify a sequence in-place by shuffling its contents.

Distributions

normal([loc, scale, size, dtype, device, out])

Draw random samples from a normal (Gaussian) distribution.

uniform([low, high, size, dtype, device, out])

Draw samples from a uniform distribution.

rand(*size, **kwargs)

Random values in a given shape.

randint(low[, high, size, dtype, device, out])

Return random integers from low (inclusive) to high (exclusive).

beta(a, b[, size, dtype, device])

Draw samples from a Beta distribution.

chisquare(df[, size, dtype, device])

Draw samples from a chi-square distribution.

exponential([scale, size, device, out])

Draw samples from an exponential distribution.

f(dfnum, dfden[, size, device])

Draw samples from an F distribution.

gamma(shape[, scale, size, dtype, device, out])

Draw samples from a Gamma distribution.

gumbel([loc, scale, size, device, out])

Draw samples from a Gumbel distribution.

laplace([loc, scale, size, dtype, device, out])

Draw random samples from a Laplace distribution.

logistic([loc, scale, size, device, out])

Draw samples from a logistic distribution.

lognormal([mean, sigma, size, dtype, …])

Draw samples from a log-normal distribution.

multinomial(n, pvals[, size])

Draw samples from a multinomial distribution.

multivariate_normal(mean, cov[, size, …])

Draw random samples from a multivariate normal distribution.

pareto(a[, size, device, out])

Draw samples from a Pareto II or Lomax distribution with specified shape a.

power(a[, size, device, out])

Draw samples in [0, 1] from a power distribution with given parameter a.

rayleigh([scale, size, device, out])

Draw samples from a Rayleigh distribution.

weibull(a[, size, device, out])

Draw samples from a 1-parameter Weibull distribution with given parameter a via inversion.