NumPy: Find the index of the sliced elements as follows from a given 4x4 array

NumPy: Array Object Exercise-122 with Solution

Write a NumPy program to find the index of the sliced elements from a given 4x4 array.

Pictorial Presentation:

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.reshape(np.arange(16), (4, 4))

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

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

# Printing a message indicating the sliced elements will be displayed
print("Sliced elements:")

# Slicing specific elements from 'x' using advanced indexing with specific row and column indices
# The selected elements are x[0, 0], x[1, 1], x[2, 3]
result = x[[0, 1, 2], [0, 1, 3]]

# Displaying the sliced elements
print(result) 

Sample Output:

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

Explanation:

x = np.reshape(np.arange(16), (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(). The array x looks like:

result = x[[0, 1, 2], [0, 1, 3]]: Use integer array indexing to select specific elements from the 2D array x. This line of code selects the elements with the following indices: (0, 0), (1, 1), and (2, 3). Integer array indexing allows you to select elements from different rows and columns by specifying their indices as lists or arrays.

print(result): Print the resulting 1D array of the selected elements:

Python-Numpy Code Editor:

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