`rand` (d0, d1, ..., dn) | Random values in a given shape. |

`randn` (d0, d1, ..., dn) | Return a sample (or samples) from the “standard normal” distribution. |

`randint` (low[, high, size, dtype]) | Return random integers from `low` (inclusive) to `high` (exclusive). |

`random_integers` (low[, high, size]) | Random integers of type np.int between `low` and `high` , inclusive. |

`random_sample` ([size]) | Return random floats in the half-open interval [0.0, 1.0). |

`random` ([size]) | Return random floats in the half-open interval [0.0, 1.0). |

`ranf` ([size]) | Return random floats in the half-open interval [0.0, 1.0). |

`sample` ([size]) | Return random floats in the half-open interval [0.0, 1.0). |

`choice` (a[, size, replace, p]) | Generates a random sample from a given 1-D array |

`bytes` (length) | Return random bytes. |

`shuffle` (x) | Modify a sequence in-place by shuffling its contents. |

`permutation` (x) | Randomly permute a sequence, or return a permuted range. |

`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, ...) | 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. |

`RandomState` | Container for the Mersenne Twister pseudo-random number generator. |

`seed` ([seed]) | Seed the generator. |

`get_state` () | Return a tuple representing the internal state of the generator. |

`set_state` (state) | Set the internal state of the generator from a tuple. |

© 2008–2017 NumPy Developers

Licensed under the NumPy License.

https://docs.scipy.org/doc/numpy-1.13.0/reference/routines.random.html