NumPy norm: How to calculate the norm of a vector in Python

This is an example to calculate a vector norm using Python NumPy.

import numpy as np
from numpy import linalg as LA

v = np.array([3, 4])

n = LA.norm(v)

print(n)  # 5.0
print(type(n))  # <class 'numpy.float64'>

linalg.norm returns the norm of NumPy array (vector) in numpy.float64. numpy.float64 is not float.

Another example.

import numpy as np
from numpy import linalg as LA

v = np.array([-1, 2.3, 1 / 5])

n = LA.norm(v)

print(n)  # 2.515949125081825
print(type(n))  # <class 'numpy.float64'>

Even if a vector has a fraction or float, norm calculates properly.