NumPy: Extract third and fourth elements of the first and second rows from a given (4x4) array
Extract Third & Fourth Elements of First Two Rows
Write a NumPy program to extract the third and fourth elements of the first and second 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 (third and fourth elements of the first and second rows)
print("\nExtracted data: Third and fourth elements of the first and second rows")
# Using slicing to extract the first two rows and columns 2 and 3 (2:4 refers to 2nd and 3rd indices)
print(arra_data[0:2, 2:4])
Sample Output:
Original array: [[ 0 1 2 3] [ 4 5 6 7] [ 8 9 10 11] [12 13 14 15]] Extracted data: Third and fourth elements of the first and second rows [[2 3] [6 7]]
Explanation:
In the above code -
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[0:2, 2:4]): It prints a subarray of ‘arra_data’ containing the first two rows and the last two columns. The slicing syntax 0:2 indicates elements from index 0 (inclusive) to index 2 (exclusive), and the slicing syntax 2:4 indicates elements from index 2 (inclusive) to index 4 (exclusive).
Python-Numpy Code Editor: