Tutorial

numpy.square() in Python

Published on August 3, 2022
author

Pankaj

numpy.square() in Python

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Python numpy.square() function returns a new array with the element value as the square of the source array elements. The source array remains unchanged.

Python numpy.square() Examples

It’s a utility function to quickly get the square of the matrix elements. Let’s look at the examples of numpy square() function with integer, float, and complex type array elements.

1. numpy square() int array

import numpy as np

# ints
array_2d = np.array([[1, 2, 3], [4, 5, 6]])

print(f'Source Array:\n{array_2d}')

array_2d_square = np.square(array_2d)

print(f'Squared Array:\n{array_2d_square}')

Output:

Source Array:
[[1 2 3]
 [4 5 6]]
Squared Array:
[[ 1  4  9]
 [16 25 36]]

2. numpy square() floating point array

import numpy as np

array_2d_float = np.array([1.2, 2.3, 5])

print(f'Source Array:\n{array_2d_float}')

array_2d_float_square = np.square(array_2d_float)

print(f'Squared Array:\n{array_2d_float_square}')

Output:

Source Array:
[1.2 2.3 5. ]
Squared Array:
[ 1.44  5.29 25.  ]

Notice that the integer in the floating-point array has been converted to a floating-point number.

3. numpy square() complex numbers array

arr = np.array([1 + 2j, 2 + 3j, 4])

print(f'Source Array:\n{arr}')

arr_square = np.square(arr)

print(f'Squared Array:\n{arr_square}')

Output:

Source Array:
[1.+2.j 2.+3.j 4.+0.j]
Squared Array:
[-3. +4.j -5.+12.j 16. +0.j]

Here the integer element is converted to a complex number. Reference: API Doc

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