NumPy: Extract first element of the second row and fourth element of fourth row from a given (4x4) array

NumPy: Array Object Exercise-143 with Solution

Write a NumPy program to extract the first element of the second row and the fourth element of the fourth row 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 (First element of the second row and fourth element of fourth row)
print("\nExtracted data: First element of the second row and fourth element of fourth row")

# Using fancy indexing to extract elements from specific rows and columns using their indices
print(arra_data[[1, 3], [0, 3]]) 

Sample Output:

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

Extracted data: First element of the second row and fourth element of fourth row  
[ 4 15]

Explanation:

In the above exercise –

arra_data = np.arange(0, 16).reshape((4, 4)): It 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]]): This line 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. The elements at the intersection of these rows and columns are extracted and create a subarray.

Python-Numpy Code Editor:

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