NumPy: Extract second and third elements of the second and third rows from a given (4x4) array

Last update on December 21 2024 08:30:27 (UTC/GMT +8 hours)

Extract Second & Third Elements of Second & Third Rows

Write a NumPy program to extract the second and third elements of the second and third rows 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 NumPy array 'arra_data' containing integers from 0 to 15 and reshaping it into a 4x4 matrix
arra_data = np.arange(0, 16).reshape((4, 4))

# Displaying a message indicating the original array will be printed
print("Original array:")

# Printing the original 4x4 array 'arra_data'
print(arra_data)

# Displaying a message indicating the extracted data (Second and third elements of the second and third rows)
print("\nExtracted data: Second and third elements of the second and third rows")

# Using slicing to extract a sub-array containing the second and third elements of the second and third rows
print(arra_data[1:3, 1:3]) 

Sample Output:

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

Extracted data: Second and third elements of the second and third rows
[[ 5  6]
 [ 9 10]]

Explanation:

arra_data = np.arange(0, 16).reshape((4, 4)): This line creates a 1-dimensional NumPy array with elements from 0 to 15 (excluding 16) using np.arange(0, 16) and then reshapes it into a 2-dimensional array with 4 rows and 4 columns using .reshape((4, 4)).

print(arra_data[[1, 3], [0, 3]]): It prints specific elements of ‘arra_data’ by selecting elements with row indices 1 and 3 and column indices 0 and 3. The indexing [1, 3] selects the second and fourth rows, and [0, 3] selects the first and fourth columns.

Python-Numpy Code Editor: