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NumPy | Create Random Valued Array

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To create an array filled with random numbers, given the shape and type of array, we can use numpy.empty() method.

Example:

Python3




import numpy as np 
    
b = np.empty(3, dtype = float
print("Matrix b : \n", b) 


Output:

[6.79249278e-310 6.79249278e-310 1.69375695e+190]

Syntax

Syntax: np.empty(shape, dtype=None, order=’C’, *, like=None)

Parameter:

  • shape : Number of rows
  • order : C_contiguous or F_contiguous
  • dtype : [optional, float(by Default)] Data type of returned array.
  • like: [optional] allows you to create an array with the same shape and data type as another array-like object

More Examples

Let’s see some examples of how to create an array with random values in NumPy.

Example 1

We create 2 NumPy arrays with random values in this example. Array ‘b’ with size 2 and array ‘a’ which is a 2D array.

Python3




# Python Program to create numpy array 
# filled with random values
import numpy as geek 
    
b = geek.empty(2, dtype = int
print("Matrix b : \n", b) 
    
a = geek.empty([2, 2], dtype = int
print("\nMatrix a : \n", a) 


Output:

Matrix b : 
 [140489599921032        21301024]

Matrix a : 
 [[140489599921048        18650592]
 [       10738656 140489568798064]]

Example 2

In this example, we create 2 random value arrays in NumPy. Array ‘c’ which is a 3×3 array and array ‘d’ which is a 5×3 array.

Python3




# Python Program to create numpy array 
# filled with random values
import numpy as geek 
  
# Python Program to create numpy array 
# filled with random values
import numpy as geek 
  
c = geek.empty([3, 3]) 
print("\nMatrix c : \n", c)
  
d = geek.empty([5, 3], dtype = int
print("\nMatrix d : \n", d)
   


Output:

Matrix c : 
 [[  1.37596097e-316   5.39314154e-317   5.39307830e-317]
 [  5.39345774e-317   5.39345774e-317   6.93325440e-310]
 [  5.39481741e-317   6.93325440e-310   8.69555537e-322]]

Matrix d : 
 [[140330665569272        23735792               0]
 [       10739936 140330589556496               0]
 [              0               0        10739904]
 [140330587337872               0        10915968]
 [              0        10739904               0]]


Last Updated : 09 Feb, 2024
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