NumPy reshape()

Summary: in this tutorial, you’ll learn how to use the numpy reshape() function to change the shape of an array.

Introduction to the numpy reshape() function

A shape of an array stores the number of dimensions (or axes) and the number of elements on each dimension. The shape property returns a tuple that describes the shape of an array.

The reshape() function changes the shape of an array without changing its elements. Here’s the syntax of the reshape() function:

numpy.reshape(a, newshape, order='C')Code language: Python (python)

In this syntax, the reshape() function changes the shape of the array a to the newshape but keep the number of elements the same.

The reshape() function is equivalent to calling the reshape() method on the array a:

a.reshape(newshape, order='C')Code language: Python (python)

NumPy reshape() function examples

Let’s take some examples of using the reshape() function.

1) Using numpy reshape() function with 1-D array example

The following example uses the numpy reshape() function to change a 1-D array with 4 elements to a 2-D array:

import numpy as np

a = np.arange(1, 5)
print(a)

b = np.reshape(a, (2, 2))
print(b)Code language: Python (python)

Output:

[1 2 3 4]
[[1 2] 
 [3 4]]Code language: Python (python)

How it works.

First, create a 1-D array with four numbers from 1 to 4 by using the arange() function:

a = np.arange(1, 5)
print(a)Code language: Python (python)

Second, change the shape of array a to an array with two dimensions, each dimension has 2 elements:

b = np.reshape(a, (2, 2))
print(b)Code language: Python (python)

2) Numpy reshape() returns a view

Note that array b is a view of array a. It means that if you change an element of array b, the change is reflected in array a. For example:

import numpy as np

a = np.arange(1, 5)
b = np.reshape(a, (2, 2))

# change the element [0,0]
b[0, 0] = 0

print(b)
print(a)Code language: Python (python)

Output:

[[0 2] 
 [3 4]]
[0 2 3 4]Code language: Python (python)

In this example, we change the element at index [0,0] in the array b. The change is also reflected in the array a.

Summary

• Use the numpy reshape() function to change the shape of an array without changing its elements.
• You can change the shape of an array as long as the number of elements is the same.