How do I calculate the Levenshtein distance between two Pandas DataFrame columns?

Question

I'm trying to calculate the Levenshtein distance between two Pandas columns but I'm getting stuck Here is the library I'm using. Here is a minimal, reproducible example:

import pandas as pd
from textdistance import levenshtein

attempts = [['passw0rd', 'pasw0rd'],
            ['passwrd', 'psword'],
            ['psw0rd', 'passwor']]

df=pd.DataFrame(attempts, columns=['password', 'attempt'])

   password  attempt
0  passw0rd  pasw0rd
1   passwrd   psword
2    psw0rd  passwor

My poor attempt:

df.apply(lambda x: levenshtein.distance(*zip(x['password'] + x['attempt'])), axis=1)

This is how the function works. It takes two strings as arguments:

levenshtein.distance('helloworld', 'heloworl')

Out[1]: 2

Answer 1

Maybe I'm missing something, is there a reason you don't like the lambda expression? This works to me:

import pandas as pd
from textdistance import levenshtein

attempts = [['passw0rd', 'pasw0rd'],
            ['passwrd', 'psword'],
            ['psw0rd', 'passwor'],
            ['helloworld', 'heloworl']]

df=pd.DataFrame(attempts, columns=['password', 'attempt'])

df.apply(lambda x: levenshtein.distance(x['password'],  x['attempt']), axis=1)

out:

0    1
1    3
2    4
3    2
dtype: int64