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這篇文章主要為大家展示了“ numpy random模塊有哪些”，內容簡而易懂，條理清晰，希望能夠幫助大家解決疑惑，下面讓小編帶領大家一起研究并學習一下“ numpy random模塊有哪些”這篇文章吧。
一下方法都要加np.random.前綴
1.簡單隨機數據
| name | describe |
|---|---|
| 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. |
2.生成隨機分布
| name | describe |
|---|---|
| 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 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. |
3.重排
| name | describe |
|---|---|
| shuffle(x) | Modify a sequence in-place by shuffling its contents. |
| permutation(x) | Randomly permute a sequence, or return a permuted range. |
以上是“ numpy random模塊有哪些”這篇文章的所有內容，感謝各位的閱讀！相信大家都有了一定的了解，希望分享的內容對大家有所幫助，如果還想學習更多知識，歡迎關注億速云行業資訊頻道！
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