NumPy: Place a specified element in specified time randomly in a specified 2D array

Last update on August 29 2025 12:45:15 (UTC/GMT +8 hours)

Place elements randomly in a 2D array.

Write a NumPy program to place a specified element in specified time randomly in a specified 2D array.

Pictorial Presentation:

Sample Solution:

Python Code:

# Importing the NumPy library
import numpy as np

# Defining variables n (size of the square array), i (number of random elements), and e (specified element)
n = 4
i = 3
e = 10

# Creating an array of zeros with shape (n, n)
array_nums1 = np.zeros((n, n))

# Displaying the original array of zeros
print("Original array:")
print(array_nums1)

# Putting the specified element 'e' in 'i' randomly chosen positions within the array
np.put(array_nums1, np.random.choice(range(n * n), i, replace=False), e)

# Displaying the array after placing the specified element 'e' in 'i' randomly chosen positions
print("\nPlace a specified element in specified time randomly:")
print(array_nums1) 

Sample Output:

Original array:
[[0. 0. 0. 0.]
 [0. 0. 0. 0.]
 [0. 0. 0. 0.]
 [0. 0. 0. 0.]]

Place a specified element in specified time randomly:
[[10.  0.  0.  0.]
 [10.  0.  0.  0.]
 [ 0.  0.  0. 10.]
 [ 0.  0.  0.  0.]]

Explanation:

In the above example -

Three variables 'n', 'i', and 'e' are assigned values 4, 3, and 10, respectively.

array_nums1 is initialized as a 2D NumPy array of zeros with shape (n, n), which in this case is (4, 4).

np.put(array_nums1, np.random.choice(range(n*n), i, replace=False), e):

In the above code -

• np.random.choice is used to randomly choose 'i' unique elements from the range of 0 to (n * n) - 1, i.e., 0 to 15.
• The parameter replace=False ensures that the elements are chosen without replacement, making them unique.
• np.put is used to replace the chosen elements in the flattened version of array_nums1 with the value 'e' (10).

For more Practice: Solve these Related Problems:

• Write a NumPy program to randomly assign a specified value to a fixed number of positions in a 2D array using np.random.choice.
• Create a function that replaces randomly selected elements in a matrix with a given number and then returns the modified array.
• Implement a solution that generates random row and column indices to insert a specified value at those locations.
• Test the random placement function on arrays with different sizes and verify that the number of replacements matches the input parameter.

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