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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?

get the square root of each element in numpy array

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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Author

  • Piyush Raj

    Piyush is a data professional passionate about using data to understand things better and make informed decisions. In the past, he's worked as a Data Scientist for ZS and holds an engineering degree from IIT Roorkee. His hobbies include watching cricket, reading, and working on side projects.