The Gaussian values are drawn from a standard Gaussian distribution this is a distribution that has a mean of 0. This function takes a single argument to specify the size of the resulting array. If you don't need the exact proportion, then the binomial approach will work just fine. An array of random Gaussian values can be generated using the randn() NumPy function. If high is None (the default), then results are from 0, low ). Table of contents Python random. Return random integers from the discrete uniform distribution of the specified dtype in the half-open interval low, high ). Return random integers from low (inclusive) to high (exclusive). The functions np.ones and np.random.random can also create two-dimensional arrays. Note that this approach will give you the exact proportion of zeros/ones you request, unlike say the binomial approach. random.randint(low, highNone, sizeNone, dtypeint). In mathematics, we often need arrays of numbers with two or more. Alias for randomsample to ease forward-porting to the new random API. It is a built-in function in the NumPy package of python. A simple way to do this would be to first generate an ndarray with the proportion of zeros and ones you want: > import numpy as np
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