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.

Table of Contents

## 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