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

Last update on April 29 2025 12:55:15 (UTC/GMT +8 hours)

9. 1D to 2D Shared Data

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.

For more Practice: Solve these Related Problems:

Write a NumPy program to demonstrate the difference between reshape (view) and copy by modifying a 1D array reshaped to 2D.
Write a NumPy program to modify a reshaped 3×3 view of a 1D array and print both arrays to show data sharing.
Write a NumPy program to extract a sub-array from a reshaped 1D array and demonstrate how changes in the sub-array reflect on the original.
Write a NumPy program to compare the memory addresses of a 1D array and its 2D reshaped view to prove they share the same data.

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