NumPy: Extract all the elements of the second row from a given (4x4) array
Extract Second Row of 4x4 Array
Write a NumPy program to extract all the elements of the second 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 (second row)
print("\nExtracted data: Second row")
# Printing the second row of the 'arra_data' array using row indexing
print(arra_data[1, :])
Sample Output:
Original array: [[ 0 1 2 3] [ 4 5 6 7] [ 8 9 10 11] [12 13 14 15]] Extracted data: Second row [4 5 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[1, :]): Here print() function prints the second row of the array arra_data. In this case, it will print [4, 5, 6, 7]. The index 1 corresponds to the second row in the array, and the colon : indicates that all columns should be included.
For more Practice: Solve these Related Problems:
- Write a NumPy program to slice out the second row from a 4x4 array and print the result.
- Create a function that extracts a specified row from a 2D array and validates the output.
- Test the extraction on various arrays to ensure that the correct row is always returned.
- Implement a solution using np.take along axis 0 to obtain the second row and compare it with slicing.
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