Random sampling in NumPy | randint () function



numpy.random.randint() — one of the functions for random sampling in numpy. It returns an array of the specified shape and fills it with random integers from low (inclusive) to high (excluding), that is, in the range [low, high).

Syntax: numpy.random.randint (low, high = None, size = None, dtype = `l`)

Parameters:
low: [int] Lowest (signed) integer to be drawn from the distribution.But, it works as a highest integer in the sample if high = None.
high: [int, optional] Largest (signed) integer to be drawn from the distribution.
size: [int or tuple of ints, optional] Output shape. If the given shape is, eg, (m, n, k), then m * n * k samples are drawn. Default is None, in which case a single value is returned.
dtype: [optional] Desired output data-type.

Return: Array of random integers in the interval [low, high) or a single such random int if size not provided.

Code # 1:

# Python program explaining
# numpy.random.randint () function

 
# numpy import

import numpy as geek

 
# output array

out_arr = geek.random.randint (low = 0 , high = 3 , size = 5 )

print ( " Output 1D Array filled with random integers: " , out_arr) 

Output:

 Output 1D Array filled with random integers: [1 1 0 1 1] 

Code # 2:

# Python program explaining
# numpy.random .randint () function

 
# numpy import

import numpy as geek

  

  
# output array

out_arr = geek.random.randint (low = 4 , size = ( 2 , 3 ))

print ( "Output 2D Array filled with random integers:" , out_arr) 

Output:

 Output 2D Array filled with random integers: [[1 1 0] [1 0 3]] 

Code # 3:

# Python program explaining
# numpy .random.randint () function

 
# numpy import

import numpy as geek

  
# output array

out_arr = geek.random.randint ( 2 , 10 , ( 2 , 3 , 4 ))

print ( "Output 3D Array filled with random integers: " , out_arr) 

Output:

 Output 3D Array filled with random integers: [[[4 8 5 7] [6 5 6 7] [4 3 4 3]] [[2 9 2 2] [3 2 2 3] [6 8 3 2]]]