NumPy square()

The numpy.square() function computes the element-wise square of the input array, returning the squared values of each element.

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numpy.square(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True)

Parameter	Type	Description
`x`	array_like	Input data whose elements will be squared.
`out`	ndarray, None, or tuple of ndarray and None, optional	Optional output array where the result is stored. If None, a new array is created.
`where`	array_like, optional	Boolean mask specifying which elements should be squared. Elements where `where=False` retain their original value.
`casting`	str, optional	Defines the casting behavior when computing the square function.
`order`	str, optional	Memory layout order of the output array.
`dtype`	data-type, optional	Defines the data type of the output array.
`subok`	bool, optional	Determines if subclasses of ndarray are preserved in the output.

Returns an array containing the element-wise square of the input values. If the input is a scalar, a scalar is returned.

Examples

Here, we compute the square of a single number using numpy.square().

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import numpy as np

# Define a number
num = 5

# Compute the square
result = np.square(num)

# Print the result
print("Square of", num, ":", result)

Square of 5 : 25