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# What is the numpy.sqrt() function in NumPy? Onyejiaku Theophilus Chidalu

Grokking Modern System Design Interview for Engineers & Managers

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### Overview

The sqrt() function in NumPy computes the non-negative square root of each element of an input array.

### Syntax

numpy.sqrt(x, /, out=None, *, where=True)
Syntax for the sqrt() function

### Parameter value

The sqrt() function takes the following parameter values:

• x: This represents an input array of values. This is a required parameter.
• out: This represents the location where the result is stored. This is an optional parameter.
• where: This is the condition over which the input is being broadcast. At a given location where this condition is True, the resulting array will be set to the ufunc result. Otherwise, the resulting array will retain its original value. This is an optional parameter.
• **kwargs: This represents other keyword arguments. This is an optional parameter.
• ### Return value

The sqrt() function returns an array of the same shape as the input array passed to it. This array holds the positive square root of the elements in it.

### Example

import numpy as np

# creating an input array of complex values
x = np.array([1, 4, 9, 16, 25, 36])

# implementing the sqrt() function
myarray = np.sqrt(x)

print(x)
print(myarray)
Implementing the sqrt() function

### Explanation

• Line 1: We import the numpy module.
• Line 4: We create an array, x, with complex values using the array() function.
• Line 7: We implement the sqrt() function on the input array and assign the result to a variable, myarray.
• Line 9: We print the variable x.
• Line 10: We print myarray.

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numpy
python
communnitycreator

CONTRIBUTOR Onyejiaku Theophilus Chidalu

Grokking Modern System Design Interview for Engineers & Managers

Ace your System Design Interview and take your career to the next level. Learn to handle the design of applications like Netflix, Quora, Facebook, Uber, and many more in a 45-min interview. Learn the RESHADED framework for architecting web-scale applications by determining requirements, constraints, and assumptions before diving into a step-by-step design process.

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