# .sqrt()

Published Jun 6, 2024
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In NumPy, the `.sqrt()` method is used to calculate the positive square root of a number or the elements of an array. It is commonly employed in mathematical computations such as solving quadratic equations, applying the Pythagorean Theorem, modelling normal distributions, and more.

## Syntax

``````numpy.sqrt(array, out=None, where=True)
``````
• `array`: A number or array-like structure containing the elements to which the method is to be applied.
• `out` (Optional): The array where the result is to be stored. If not provided, a new array is created and used for storing the results.
• `where` (Optional): The condition (array of boolean values) that determines the elements on which the method is to be applied.
• If the condition is `True` for a particular element, the square root is computed for that element.
• If the condition is `False` for a particular element, the square root is not computed for that element and the original element is retained.
• If not provided, the square root is computed for all elements.

## Example

The below example shows the `.sqrt()` method in use:

```# Importing the 'numpy' library as 'np'import numpy as np
# Computing the square root of only those elements in the array which is greater than or equal to 5result = np.sqrt([9,-4,25], where=np.array([9,-4,25]) >= 5)
print(result)
```

The output of the above code is shown below:

```[3.00000000e+000 6.50227506e-310 5.00000000e+000]
```

## Codebyte Example

In this codebyte example, the `.sqrt()` method only computes the square root of the elements of the array which are greater than 0:

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