NumPy: Extract second and fourth elements of the second and fourth rows from a given (4x4) array
Extract Second & Fourth Elements of Second/Fourth Rows
Write a NumPy program to extract the second and fourth elements of the second and fourth 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 fourth elements of the second and fourth rows)
print("\nExtracted data: Second and fourth elements of the second and fourth rows")
# Using slicing to extract the second and fourth elements of every other row and column starting from the second row and second column
print(arra_data[1::2, 1::2])
Sample Output:
Original array: [[ 0 1 2 3] [ 4 5 6 7] [ 8 9 10 11] [12 13 14 15]] Extracted data: Second and fourth elements of the second and fourth rows [[ 5 7] [13 15]]
Explanation:
. In the above example -
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::2, 1::2]): It prints specific elements of ‘arra_data’ by selecting every second row starting from the second row (index 1) and every second column starting from the second column (index 1) using the slicing syntax 1::2.
Python-Numpy Code Editor:
What is the difficulty level of this exercise?
Test your Programming skills with w3resource's quiz.
- Weekly Trends and Language Statistics
- Weekly Trends and Language Statistics