# Python NumPy Square Root

Python `numpy.sqrt()` function is used to return the non-negative square root of an array element-wise (for each element of the array). In this article, I will explain how to use Numpy square root by using `numpy.sqrt()` function with examples.

## 1. Quick Examples of Python NumPy Square Root

If you are in a hurry, below are some quick examples of how to use Python NumPy square root function.

``````
# Below are a quick examples

# Example 1: numpy.sqrt() of single element
arr2 = np.sqrt(45)

# Example 2: Use numpy.sqrt() function to square root of numbers
arr = [25, 49, 225, 64, 81, 16]
arr2 = np.sqrt(arr)

# Example 3: Use numpy.sqrt() function with complex numbers
arr = [2+6j, -5-8j, 4-5j, 3+4j]
arr2 = np.sqrt(arr)

# Example 4: Use numpy.sqrt() function with negative and inifite as input values
arr = [-6, np.inf, 25, -15, np.inf]
arr2 = np.sqrt(arr)

# Example 5: Use numpy.sqrt() function to floating-point array
arr = [4.3, 8.5, 15.1, 23.7, 14.2, 7.8]
arr2 = np.sqrt(arr)

# Example 6: Use numpy.sqrt() function to square root from multiple array
arr = np.array([[25, 64, 9, 16], [9, 4, 49, 36]])
arr2 = np.sqrt(arr)
``````

## 2. Syntax Python NumPy Square Root

Following is the syntax of the `numpy.sqrt()` function.

``````
# Syntax of python numpy.sqrt()
numpy.sqrt(arr, out=None, where=True, casting='same_kind', order='K', dtype=None)
``````

### 2.1 Parameters of sqrt()

• `arr` – The values whose square-roots are required. Input array.
• `out` – It is ndarray, None, or tuple of ndarray and None, optional. Out will be the location where the result is to be stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned.
• `where` – It is array_like, optional. This condition is broadcast over the input.

### 2.2 Return Value of sqrt()

`Return`: It returns an array of the square root of the number in the input array.

## 3. Usage of NumPy Square Root Function

You can get the square root of the single element of an array using `numpy.sqrt()` function. You can also get the square values of the NumPy array using `numpy.square()`.

``````
import numpy as np

# Create a single element
arr = np.array(25)

# Use numpy.sqrt() function to get single element
arr2 = np.sqrt(arr)
print(arr2)

# Output:
[5.0]

# get single element square root value
arr2 = np.sqrt(45)
print(arr2)

# Output :
# 6.708203932499369
``````

## 4. Get the Multiple Square Root Values of NumPy Array

To initialize the array with list of numbers use `numpy.array()` and calculate the square root of these numbers by using the `numpy.sqrt()` function. For example,

``````
# Create an input array
arr =np.array([25, 49, 225, 64, 81, 16])

# Use numpy.sqrt() function to square root of numbers
arr2 = np.sqrt(arr)
print(arr2)

# Output
# [ 5.  7. 15.  8.  9.  4.]
``````

## 5. Get the Square Roots of Complex Numbers

You can use complex numbers as elements of an array to calculate the square roots of these elements using `numpy.sqrt()`. For example,

``````
# Create an input array
arr =np.array( [2+6j, -5-8j, 4-5j, 3+4j])

# Use numpy.sqrt() function with complex numbers
arr2 = np.sqrt(arr)
print(arr2)

# Output
# [2.04016609+1.47046852j 1.4889562 -2.68644571j 2.28069334-1.09615789j  2.+1.j ]
``````

## 6. Get The Square Roots of Negative and Infinite Values

Using the` numpy.sqrt()` function you can also calculate the square root of the negative and Infinite as input values of an array. The square root of a matrix with negative numbers will throw RuntimeWarning and the square root of the element is returned as `nan` as a result.

``````
# Create an 1D input array
arr =np.array[-6, np.inf, 25, -15, np.inf]

# Use numpy.sqrt() function with negative and infinite
arr2 = np.sqrt(arr)
print(arr2)

# Output
# [nan inf  5. nan inf]
# RuntimeWarning: invalid value encountered in sqrt
``````

## 7. Get the Square root of NumPy Array with Float Values

You can find the square root of the float values of array elements by using the `numpy.sqrt()` function.

``````
# Create an 1D input array
arr = np.array( [4.3, 8.5, 15.1, 23.7, 14.2, 7.8])

# Use numpy.sqrt() function to floating-point array
arr2 = np.sqrt(arr)
print(arr2)

# Output
# [2.07364414 2.91547595 3.88587185 4.86826458 3.76828874 2.79284801]
``````

## 8. Get the Square Roots of 2-D NumPy Array Values

Let’s calculate the square roots 2-D NumPy array values by using `numpy.sqrt()` function.

``````
# Create an 2D input array
arr = np.array([[25, 64, 9, 16], [9, 4, 49, 36]])

# Use numpy.sqrt() function to get the
# square root values of 2-d array
arr2 = np.sqrt(arr)
print(arr2)

# Output
# [[5. 8. 3. 4.]
# [3. 2. 7. 6.]]
``````

## 9. Conclusion

In this article, I have explained how to use Python `numpy.sqrt()` function to calculate the square root of every element in the given array with examples.

Happy Learning!!

## References 