How can the Euclidean distance be calculated with NumPy?

Solution 1:

Use numpy.linalg.norm:

dist = numpy.linalg.norm(a-b)

You can find the theory behind this in Introduction to Data Mining

This works because the Euclidean distance is the l2 norm, and the default value of the ord parameter in numpy.linalg.norm is 2.

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There's a function for that in SciPy. It's called Euclidean.

Example:

from scipy.spatial import distance
a = (1, 2, 3)
b = (4, 5, 6)
dst = distance.euclidean(a, b)