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 –
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
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)
[1 0 4 9]
Here, we used the
numpy.array() function to create a Numpy array containing some numbers.
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Step 2 – Get the square root using
To get the square root of each element in a Numpy array, pass the array as an argument to the
Let’s get the square root for the array created above.
# get the square root of each element np.sqrt(ar)
array([1., 0., 2., 3.])
We get a Numpy array with the square root value of each element in the array
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)
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.
You might also be interested in –
- Numpy – Get the Sign of Each Element in Array
- Get the Median of Numpy Array – (With Examples)
- Numpy – Get Standard Deviation of Array Values
- Numpy – Get Min Value in Array
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