How to compute the euclidean distance between two arrays in numpy
This recipe helps you compute the euclidean distance between two arrays in numpy
Recipe Objective
How to compute the euclidean distance between two arrays?
Euclidean distance is the distance between two points for e.g point A and point B in the euclidean space. This distance can be found in the numpy by using the function "linalg.norm". Let's understand this with practical implementation.
Table of Contents
Step 1 - Import library
import numpy as np
Step 2 - Take Sample data
data_pointA = np.array([5,6,7])
data_pointB = np.array([8,9,10])
Step 3 - Find Euclidean distance
Euclidean_distance = np.linalg.norm(data_pointA - data_pointB)
print("The Euclidean distance between two points are:", Euclidean_distance)
The Euclidean distance between two points are: 5.196152422706632
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