Python: NumPy reshape examples

In NumPy, the reshape function is used to change the shape of an array without changing its data. Here are some examples of using reshape with different scenarios:

Example 1: Basic Reshape

import numpy as np

# Create a 1D array
arr_1d = np.array([1, 2, 3, 4, 5, 6])

# Reshape to a 2D array with 2 rows and 3 columns
arr_2d = arr_1d.reshape((2, 3))

print("Original 1D array:")
print(arr_1d)
print("\nReshaped 2D array:")
print(arr_2d)

Output:

Original 1D array:
[1 2 3 4 5 6]

Reshaped 2D array:
[[1 2 3]
 [4 5 6]]

Example 2: Reshape with -1

Using -1 as one of the dimensions allows NumPy to automatically calculate the size of that dimension based on the size of the original array.

import numpy as np

# Create a 1D array with 12 elements
arr_1d = np.arange(1, 13)

# Reshape to a 2D array with 3 rows and an automatically calculated number of columns
arr_2d = arr_1d.reshape((3, -1))

print("Original 1D array:")
print(arr_1d)
print("\nReshaped 2D array:")
print(arr_2d)

Output:

Original 1D array:
[ 1  2  3  4  5  6  7  8  9 10 11 12]

Reshaped 2D array:
[[ 1  2  3  4]
 [ 5  6  7  8]
 [ 9 10 11 12]]

Example 3: Reshape for 3D Array

import numpy as np

# Create a 1D array with 24 elements
arr_1d = np.arange(1, 25)

# Reshape to a 3D array with 2 planes, 3 rows, and 4 columns
arr_3d = arr_1d.reshape((2, 3, 4))

print("Original 1D array:")
print(arr_1d)
print("\nReshaped 3D array:")
print(arr_3d)

Output:

Original 1D 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]

Reshaped 3D 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]]]

These examples showcase different use cases for reshaping arrays using the reshape function in NumPy. Adjust the dimensions and content of the arrays based on your specific requirements.