Return Similarity Matrix From Two Variable-length Arrays Of Strings (scipy Option?)

Say I have two arrays: import numpy as np arr1 = np.array(['faucet', 'faucets', 'bath', 'parts', 'bathroom']) arr2 = np.array(['faucett', 'faucetd', 'bth', 'kichen']) and I want t

Solution 1:

I think you're looking for cdist:

import pandas as pd
import numpy as np
from scipy.spatial.distance import cdist
from Levenshtein import ratio

arr1 = np.array(['faucet', 'faucets', 'bath', 'parts', 'bathroom'])
arr2 = np.array(['faucett', 'faucetd', 'bth', 'kichen'])

matrix = cdist(arr2.reshape(-1, 1), arr1.reshape(-1, 1), lambda x, y: ratio(x[0], y[0]))
df = pd.DataFrame(data=matrix, index=arr2, columns=arr1)

Result:

           faucet   faucets      bath     parts  bathroom
faucett  0.923077  0.857143  0.363636  0.333333  0.266667
faucetd  0.923077  0.857143  0.363636  0.333333  0.266667
bth      0.222222  0.200000  0.857143  0.250000  0.545455
kichen   0.333333  0.307692  0.200000  0.000000  0.142857