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numpy.random.randn() in Python
  • Difficulty Level : Basic
  • Last Updated : 23 Oct, 2020

The numpy.random.randn() function creates an array of specified shape and fills it with random values as per standard normal distribution.

If positive arguments are provided, randn generates an array of shape (d0, d1, …, dn), filled with random floats sampled from a univariate “normal” (Gaussian) distribution of mean 0 and variance 1 (if any of the d_i are floats, they are first converted to integers by truncation). A single float randomly sampled from the distribution is returned if no argument is provided.

Syntax :

numpy.random.randn(d0, d1, ..., dn)

Parameters :

d0, d1, ..., dn : [int, optional]Dimension of the returned array we require, 
     If no argument is given a single Python float is returned.

Return :



Array of defined shape, filled with random floating-point samples from 
the standard normal distribution.

Code 1 : randomly constructing 1D array




# Python Program illustrating
# numpy.random.randn() method
   
import numpy as geek
   
# 1D Array
array = geek.random.randn(5)
print("1D Array filled with random values : \n", array);


Output :

1D Array filled with randnom values : 
 [-0.51733692  0.48813676 -0.88147002  1.12901958  0.68026197]

Code 2 : randomly constructing 2D array




# Python Program illustrating
# numpy.random.randn() method
   
import numpy as geek
   
# 2D Array   
array = geek.random.randn(3, 4)
print("2D Array filled with random values : \n", array);


Output :

2D Array filled with random values : 
 [[ 1.33262386 -0.88922967 -0.07056098  0.27340112]
 [ 1.00664965 -0.68443807  0.43801295 -0.35874714]
 [-0.19289416 -0.42746963 -1.80435223  0.02751727]]

Code 3 : randomly constructing 3D array




# Python Program illustrating
# numpy.random.randn() method
   
import numpy as geek
   
# 3D Array     
array = geek.random.randn(2, 2 ,2)
print("3D Array filled with random values : \n", array);


Output :

3D Array filled with random values : 
 [[[-0.00416587 -0.66211158]
  [-0.97254293 -0.68981333]]

 [[-0.18304476 -0.8371425 ]
  [ 2.18985366 -0.9740637 ]]]


Code 4 : Manipulations with randomly created array




# Python Program illustrating
# numpy.random.randn() method
   
import numpy as geek
   
# 3D Array     
array = geek.random.randn(2, 2 ,2)
print("3D Array filled with random values : \n", array);
       
# Multiplying values with 3
print("\nArray * 3 : \n", array *3)
  
# Or we cab directly do so by 
array = geek.random.randn(2, 2 ,2) * 3 + 2
print("\nArray * 3 + 2 : \n", array);


Output :

3D Array filled with random values : 
 [[[ 1.9609643  -1.89882763]
  [ 0.52252173  0.08159455]]

 [[-0.6060213  -0.86759247]
  [ 0.53870235 -0.77388125]]]

Array * 3 : 
 [[[ 5.88289289 -5.69648288]
  [ 1.56756519  0.24478366]]

 [[-1.81806391 -2.6027774 ]
  [ 1.61610704 -2.32164376]]]

Array * 3 + 2 : 
 [[[-2.73766306  6.80761741]
  [-1.57909191 -1.64195796]]

 [[ 0.51019498  1.30017345]
  [ 3.8107863  -4.07438963]]]

References :
https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.random.randn.html

Note :
These codes won’t run on online-ID. Please run them on your systems to explore the working.
.
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