How to flatten and reshape a 2D NumPy array?

Last update on December 21 2024 07:36:54 (UTC/GMT +8 hours)

Write a NumPy program that creates a 2D array of shape (5, 5) and use ravel() to get a flattened array. Then use reshape() to convert it back to its original shape and print both arrays.

Sample Solution:

Python Code:

import numpy as np

# Create a 2D array of shape (5, 5)
array_2d = np.array([[1, 2, 3, 4, 5],
                     [6, 7, 8, 9, 10],
                     [11, 12, 13, 14, 15],
                     [16, 17, 18, 19, 20],
                     [21, 22, 23, 24, 25]])

# Use ravel() to get a flattened array
flattened_array = array_2d.ravel()

# Print the flattened array
print("Flattened array:", flattened_array)

# Use reshape() to convert it back to its original shape
reshaped_array = flattened_array.reshape(5, 5)

# Print the reshaped array
print("Reshaped array:\n", reshaped_array)

Output:

Flattened array: [ 1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
 25]
Reshaped array:
 [[ 1  2  3  4  5]
 [ 6  7  8  9 10]
 [11 12 13 14 15]
 [16 17 18 19 20]
 [21 22 23 24 25]]

Explanation:

• Import NumPy library: We start by importing the NumPy library to handle array operations.
• Create a 2D array: We create a 2D array array_2d of shape (5, 5) using np.array().
• Flatten the array: We use the ravel() method to get a flattened 1D array from array_2d, stored in flattened_array.
• Print the flattened array: We print the flattened_array to see the flattened version of the original array.
• Reshape to original shape: We use the reshape() method to convert flattened_array back to its original shape (5, 5), resulting in reshaped_array.
• Print the reshaped array: Finally, we print the reshaped_array to verify it matches the original array's shape.

Python-Numpy Code Editor: