How to reshape and modify a 1D NumPy array to a 3x3 matrix?

Last update on December 21 2024 07:40:07 (UTC/GMT +8 hours)

Write a NumPy program that creates a 1D array of 9 elements and reshape it into a 3x3 matrix. Modify the matrix and observe the changes in the original array.

Sample Solution:

Python Code:

import numpy as np

# Create a 1D array of 9 elements
array_1d = np.arange(1, 10)

# Reshape the 1D array into a 3x3 matrix
matrix_3x3 = array_1d.reshape(3, 3)

# Modify the matrix
matrix_3x3[0, 0] = 99

# Print the modified matrix
print("Modified matrix:\n", matrix_3x3)

# Print the original 1D array to observe changes
print("Original 1D array after modification:", array_1d)

Output:

Modified matrix:
 [[99  2  3]
 [ 4  5  6]
 [ 7  8  9]]
Original 1D array after modification: [99  2  3  4  5  6  7  8  9]

Explanation:

• Import NumPy library: We start by importing the NumPy library to handle array operations.
• Create a 1D array: We create a 1D array array_1d with 9 elements using np.arange(1, 10).
• Reshape to a 3x3 matrix: We reshape the 1D array to a 3x3 matrix matrix_3x3 using reshape().
• Modify the matrix: We change the first element of the matrix to 99.
• Print the modified matrix: We print the modified matrix to see the change.
• Observe changes in the original array: We print the original 1D array to observe that the modification in the matrix also affects the original array since they share the same data.

Python-Numpy Code Editor: