Reshape Array in NumPy - Python Examples

Contents

Introduction
Examples
Summary

NumPy – Reshape Array

To reshape a given array to specific shape using NumPy library, we can use numpy.reshape() function.

Pass the given array, and required shape (as tuple) as arguments to the numpy.reshape() function.

Examples

In the following program, we reshape a numpy array of shape (3, 4) to (2, 6).

Python Program

import numpy as np

# reshape (3, 4) array to (6, 2)
arr = np.array([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]])

shape = (6, 2)
output = np.reshape(arr, shape)

print(output)

Run

Output

[[ 1  2]
 [ 3  4]
 [ 5  6]
 [ 7  8]
 [ 9 10]
 [11 12]]

If any of the dimension in the input shape is given as -1, then this dimension is adjusted based on the length in other dimensions.

For example, in the following program, we reshape a numpy array of shape (3, 4) to (-1, 2). Since we have -1 for the first dimension in the output shape, that dimension’s length is computed from (3*4)/(2) which is 6.

Python Program

import numpy as np

# reshape (3, 4) array to (6, 2)
arr = np.array([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]])

shape = (-1, 2)
output = np.reshape(arr, shape)

print(output)

Run

Output

[[ 1  2]
 [ 3  4]
 [ 5  6]
 [ 7  8]
 [ 9 10]
 [11 12]]

Summary

In this tutorial of Python Examples, we learned how to reshape a given numpy array in Python using numpy.reshape() function.