A RetroSearch Logo

Home - News ( United States | United Kingdom | Italy | Germany ) - Football scores

Search Query:

Showing content from https://docs.scipy.org/doc/numpy-1.16.0/reference/routines.random.html below:

Random sampling (numpy.random) — NumPy v1.16 Manual

beta(a, b[, size]) Draw samples from a Beta distribution. binomial(n, p[, size]) Draw samples from a binomial distribution. chisquare(df[, size]) Draw samples from a chi-square distribution. dirichlet(alpha[, size]) Draw samples from the Dirichlet distribution. exponential([scale, size]) Draw samples from an exponential distribution. f(dfnum, dfden[, size]) Draw samples from an 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]) Draw samples from a Gumbel distribution. hypergeometric(ngood, nbad, nsample[, size]) Draw samples from a Hypergeometric distribution. laplace([loc, scale, size]) Draw samples from the Laplace or double exponential distribution with specified location (or mean) and scale (decay). logistic([loc, scale, size]) Draw samples from a logistic distribution. lognormal([mean, sigma, size]) Draw samples 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, â€¦) Draw random samples from a multivariate normal distribution. negative_binomial(n, p[, size]) Draw samples from a negative binomial distribution. noncentral_chisquare(df, nonc[, size]) Draw samples from a noncentral chi-square distribution. noncentral_f(dfnum, dfden, nonc[, size]) Draw samples from the noncentral F distribution. normal([loc, scale, size]) Draw random samples from a normal (Gaussian) distribution. pareto(a[, size]) Draw samples from a Pareto II or Lomax distribution with specified shape. poisson([lam, size]) Draw samples from a Poisson distribution. power(a[, size]) Draws samples in [0, 1] from a power distribution with positive exponent a - 1. rayleigh([scale, size]) Draw samples from a Rayleigh distribution. standard_cauchy([size]) Draw samples from a standard Cauchy distribution with mode = 0. standard_exponential([size]) Draw samples from the standard exponential distribution. standard_gamma(shape[, size]) Draw samples from a standard Gamma distribution. standard_normal([size]) Draw samples from a standard Normal distribution (mean=0, stdev=1). standard_t(df[, size]) Draw samples from a standard Student’s t distribution with df degrees of freedom. triangular(left, mode, right[, size]) Draw samples from the triangular distribution over the interval [left, 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]) Draw samples from a Wald, or inverse Gaussian, distribution. weibull(a[, size]) Draw samples from a Weibull distribution. zipf(a[, size]) Draw samples from a Zipf distribution.

RetroSearch is an open source project built by @garambo | Open a GitHub Issue

Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo

HTML: 3.2 | Encoding: UTF-8 | Version: 0.7.4