NumPy: Extract first element of the second row and fourth element of fourth row from a given (4x4) array
Extract First Element of Second Row & Fourth of Fourth Row
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: