# Numpy – Get the Square of Each Element in Array

The Numpy library in Python comes with a number of built-in functions to perform common mathematical operations on arrays. In this tutorial, we will look at one such function that helps us get the element-wise square of a Numpy array with the help of some examples.

## How to get the square value in Numpy?

You can use the `numpy.square()` function to get the square of each element in a Numpy array. Pass the array as an argument.

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The following is the syntax –

`numpy.square(ar)`

It returns an array containing the square value of each element in the passed array.

Let’s now look at a step-by-step example of using the `numpy.square()` function.

### Step 1 – Create a Numpy array

First, we will create a Numpy array that we will use throughout this tutorial.

```import numpy as np

# create numpy array
ar = np.array([-2, -1, 0, 1, 2, 3])
# display the array
print(ar)```

Output:

`[-2 -1  0  1  2  3]`

Here, we used the `numpy.array()` function to create a Numpy array containing some numbers. You can see that this array contains both positive and negative numbers (along with a 0).

### Step 2 – Get the square using `numpy.square()`

To get the square value of each element in a Numpy array, pass the array as an argument to the `numpy.square()` function.

Let’s get the square for the array created above.

```# get the square of each element
np.square(ar)```

Output:

`array([4, 1, 0, 1, 4, 9])`

We get a Numpy array with the square value of each element in the array `ar`.

The `numpy.square()` function works similarly on higher-dimensional arrays. For example, let’s apply this function to a 2D array of some numbers.

```# create 2D numpy array
ar = np.array([[-1, -2, -3],
[0, 5, 0],
[1, 2, 3]])
# get the sqaure of each element
np.square(ar)```

Output:

```array([[ 1,  4,  9],
[ 0, 25,  0],
[ 1,  4,  9]])```

You can see that we get the square value of each element in the 2D array.

For more on the `numpy.square()` function, refer to its documentation.

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