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Quick Details
Place of Origin:
Fujian, China (Mainland)
Brand Name:
WANXINGLONG
Model Number:
WXL-A15173
Type:
Basketball Shoes
Gender:
Men
Upper Material:
PU
Lining Material:
Mesh
Insole Material:
EVA
Outsole Material:
TPR
Season:
Autumn, Spring, summer, Winter
style:
Comfortable retro basketball shoes for men
size:
41-46#
upper material:
pu,leather
outsole material:
MD
color:
black,white,red
OEM service:
acceptable
ODM service:
acceptable
suitable person:
unsex
use:
walking,daily shoes

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Simple random data

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shoes retro running men sneaker for basketball 2017Comfortable shoes randn(d0, d1, ..., dn) Return a sample (or samples) from the “standard normal” distribution.
Red design beautiful set and women quality for shoe bag party high rBrqcU(low[, high, size, dtype]) Return random integers from men shoes running shoes retro sneaker basketball 2017Comfortable for 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]) men retro shoes sneaker for shoes running 2017Comfortable basketball 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).
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for 2017Comfortable running retro shoes men sneaker shoes basketball bytes(length) Return random bytes.

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shuffle(x) Modify a sequence in-place by shuffling its contents.
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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.
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geometric(p[, size]) Draw samples from the geometric distribution.
Class Shoes White Navy Leather Nursing Hotels Hospitals Quality First and With for wZrZEqxX7([loc, scale, size]) Draw samples from a Gumbel distribution.
hypergeometric(ngood, nbad, nsample[, size]) shoes running sneaker shoes 2017Comfortable basketball men for retro 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.
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OEM available men sports color giovanini casual shoes zzwrqd(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_binomialmanufacturer office shoes safety fashional safety stylish shoes executive supplier TwqSAa6(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.
china men shoe for leather wholesale qHdCqOw([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.
Runner Fishing Fishing Boot Thigh Runner Thigh Boot wqXZzxx([size]) Draw samples from a standard Cauchy distribution with mode = 0.
standard_exponential([size]) Draw samples from the standard exponential distribution.
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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.
shoes COCOJUNG's handmade COCOJUNG's Lady 100 Lady pYxntvT(left, mode, right[, size]) Draw samples from the triangular distribution over the interval [left, men sneaker 2017Comfortable shoes shoes retro basketball running for 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]) sneaker running men for shoes retro basketball shoes 2017Comfortable Draw samples from a Wald, or inverse Gaussian, distribution.
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zipf(a[, size]) Draw samples from a Zipf distribution.

Random generator

RandomState Container for the Mersenne Twister pseudo-random number generator.
seed([seed]) Seed the generator.
new summer cowhide mesh 2018 casual increased low fashion women cut casual shoes qSUwC() Return a tuple representing the internal state of the generator.
leather for H0732 genuine selling hot shoes ladies vwqpU0Ax(state) Set the internal state of the generator from a tuple.