NumPy: Create two arrays of size bigger and smaller than a given array

NumPy: Array Object Exercise-123 with Solution

Write a NumPy program to create two arrays bigger and smaller than a given array.

Sample Solution:

Python Code:

# Importing the NumPy library and aliasing it as 'np'
import numpy as np

# Creating a 4x4 array 'x' with elements from 0 to 15 using np.arange() and reshaping it to a 4x4 array
x = np.arange(16).reshape(4, 4)

# Printing a message indicating the original array will be displayed
print("Original array:")

# Displaying the original 4x4 array 'x'
print(x)

# Printing a message indicating the creation of a 2x2 array from the original array
print("\nArray with size 2x2 from the original array:")

# Creating a new 2x2 array 'new_array1' using np.resize() from the original array 'x'
new_array1 = np.resize(x, (2, 2))

# Displaying the new 2x2 array 'new_array1'
print(new_array1)

# Printing a message indicating the creation of a 6x6 array from the original array
print("\nArray with size 6x6 from the original array:")

# Creating a new 6x6 array 'new_array2' using np.resize() from the original array 'x'
# The elements will be repeated if necessary to fill the new size
new_array2 = np.resize(x, (6, 6))

# Displaying the new 6x6 array 'new_array2'
print(new_array2) 

Sample Output:

Original arrays:
[[ 0  1  2  3]
 [ 4  5  6  7]
 [ 8  9 10 11]
 [12 13 14 15]]

Array with size 2x2 from the said array:
[[0 1]
 [2 3]]

Array with size 6x6 from the said array:
[[ 0  1  2  3  4  5]
 [ 6  7  8  9 10 11]
 [12 13 14 15  0  1]
 [ 2  3  4  5  6  7]
 [ 8  9 10 11 12 13]
 [14 15  0  1  2  3]]

Explanation:

x = np.arange(16).reshape(4, 4): Create a 1D NumPy array of integers from 0 to 15 using np.arange(16), and then reshape it into a 4x4 2D array using np.reshape().

new_array1 = np.resize(x, (2, 2)): Resize the 4x4 2D array x to a 2x2 2D array using np.resize(). The function takes the input array and the desired shape as arguments.

new_array2 = np.resize(x, (6, 6)): Resize the 4x4 2D array x to a 6x6 2D array using np.resize().

Pictorial Presentation:

Python-Numpy Code Editor:

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