Return the non-negative square-root of an array element-wise in Numpy

To return the non-negative square-root of an array, element-wise, use the numpy.sqrt() method in Python Numpy.

An array of the same shape as x, containing the positive square-root of each element in x. If any element in x is complex, a complex array is returned (and the square-roots of negative reals are calculated). If all of the elements in x are real, so is y, with negative elements returning nan. If out was provided, y is a reference to it. This is a scalar if x is a scalar.

The out is a location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.

Steps

At first, import the required library −

import numpy as np

Create an array using the array() method −

arr = np.array([4, 9, 10000, 100, 841, 225])

Display the array −

print("Array...
", arr)

Get the type of the array −

print("
Our Array type...
", arr.dtype)

Get the dimensions of the Array −

print("
Our Array Dimension...
",arr.ndim)

Get the shape of the Array −

print("
Our Array Shape...
",arr.shape)

To return the non-negative square-root of an array, element-wise, use the numpy.sqrt() method −

print("
Result...
",np.sqrt(arr))

Example

import numpy as np

# Create an array using the array() method
arr = np.array([4, 9, 10000, 100, 841, 225])

# Display the array
print("Array...
", arr)

# Get the type of the array
print("
Our Array type...
", arr.dtype)

# Get the dimensions of the Array
print("
Our Array Dimension...
",arr.ndim)

# Get the shape of the Array
print("
Our Array Shape...
",arr.shape)

# To return the non-negative square-root of an array, element-wise, use the numpy.sqrt() method in Python Numpy
print("
Result...
",np.sqrt(arr))

Output

Array...
[ 4 9 10000 100 841 225]

Our Array type...
int64

Our Array Dimension...
1

Our Array Shape...
(6,)

Result...
[ 2. 3. 100. 10. 29. 15.]