Return a sample (or samples) from the “standard normal” distribution.

Create an array of the given shape and propagate it with random samples from a “normal”
(Gaussian) distribution of mean 0 and variance 1.
Parameters:d1, .., dn (d0,) – (int) optional. The dimensions of the returned array, should all be positive. If no argument is given a single Python float is returned.
Returns:Random values array.


>>> random.randn(3,2)
array([[-0.16930188565311702, 0.14022386771529866]
      [-0.8445258136512078, 0.20906704358209086]
      [-1.157825603461335, -2.441255068283659]])