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)
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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)
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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)
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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]]