# Numpy – Get the Square Root 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 root of a Numpy array with the help of some examples.

## How to get the square root in Numpy?

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

The following is the syntax –

`numpy.sqrt(ar)`

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

Let’s now look at a step-by-step example of using the `numpy.sqrt()` 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([1, 0, 4, 9])
# display the array
print(ar)```

Output:

`[1 0 4 9]`

Here, we used the `numpy.array()` function to create a Numpy array containing some numbers.

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

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

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

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

Output:

`array([1., 0., 2., 3.])`

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

The `numpy.sqrt()` 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([[4, 9, 4],
[0, 16, 0],
[1, 25, 4]])
# get the square root of each element
np.sqrt(ar)```

Output:

```array([[2., 3., 2.],
[0., 4., 0.],
[1., 5., 2.]])```

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

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

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