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.


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.


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 5
result = np.sqrt([9,-4,25], where=np.array([9,-4,25]) >= 5)

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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