Twitter 
Facebook
chevron_left
Cookbooks
Accessing a value in a 2D arrayAccessing columns of a 2D arrayAccessing rows of a 2D arrayCalculating the determinant of a matrixChecking allowed values for a NumPy data typeChecking if a NumPy array is a view or copyChecking the version of NumPyChecking whether a NumPy array contains a given rowComputing Euclidean distance using NumpyConcatenating 1D arraysConverting array to lowercaseConverting type of NumPy array to stringCreating a copy of an arrayDifference between Python List and Numpy arrayDifference between the methods array_equal and array_equivDifference between the methods mod and fmodDifference between the methods power and float_powerFinding the closest value in an arrayFinding the Index of Largest Value in a Numpy ArrayFinding the Index of Smallest Value in a Numpy ArrayFinding the most frequent value in a NumPy arrayFlattening Numpy arraysGetting constant PiGetting elements from a two dimensional array using two dimensional array of indicesGetting indices of N maximum valuesGetting indices of N minimum valuesGetting the number of columns of a 2D arrayGetting the number of non-zero elements in a NumPy arrayGetting the number of rows of a 2D arrayInitializing an array of onesInitializing an array of zerosInitializing an identity matrixLimiting array values to a certain rangePerforming linear regressionPrinting full or truncated NumPy arrayPrinting large Numpy arrays without truncationRemoving rows containing NaN in a NumPy arrayReversing a NumPy arraySaving NumPy array to a fileShape of Numpy ArraysSorting value of one array according to anotherSuppressing scientific notation
0
0
0
new
Computing Euclidean distance using NumPy
Programming
chevron_rightPython
chevron_rightNumPy
chevron_rightCookbooks
schedule Mar 10, 2022
Last updated Python●NumPy
Tags tocTable of Contents
expand_more To compute the Euclidean distance between two vectors in NumPy, use the np.linalg.norm(~) method like follows:
2.8284271247461903
Without providing additional parameters, the np.linalg.norm(~) method computes the L2 norm, which is equivalent to the Euclidean distance.
Published by Isshin Inada
Edited by 0 others
Did you find this page useful?
Ask a question or leave a feedback...
