Finding the euclidean distance with SciPy

Instead of writing multiple lines of code to calculate the euclidean distance, you can use SciPy. The library not only contains the euclidean function, but more than 40 other distance metrics—all a single import statement away.

This exercise is part of the course

Anomaly Detection in Python

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Exercise instructions

Import the euclidean function from the relevant scipy module.
Use the euclidean() function on M and N.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Import the euclidean function from scipy
from scipy.____.____ import euclidean

M = np.array([14, 17, 18, 20, 14, 12, 19, 13, 17, 20])
N = np.array([63, 74, 76, 72, 64, 75, 75, 61, 50, 53])

# Use the euclidean function on M and N
dist_MN = ____

print(dist_MN)

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