CODEWITHSUNDEEP
pythonpandas
Bob
Bob

Reputation: 415

Iterate over 2 dataframes and match columns for N% of similarity

I am trying to find similar strings in 2 different pandas dataframes using fuzzywuzzy.

So far all I can think of is to iterate over each frame and then use fuzz.ratio(v1, v2) to return a % of similarity.

Logic like this:

for v1_df1, v2_df1 in df1[['given_name', 'surname']].itertuples(index=False):
    for v1_df2, v2_df2 in df2[['given_name', 'surname']].itertuples(index=False):

        ratio_v1 = fuzz.ratio(v1_df1, v1_df2)

This is not suitable, but hopefully, it demonstrates what I'm trying to do. I would like an effective way to match string on two separate pandas data frames and conditionally deem them similar given a configurable %

Upvotes: 0

Views: 48

Answers (1)

Pygirl
Pygirl

Reputation: 13349

Say

df1:

    Name    First_Name
0   Lara    Owlen
1   Heiberg Lanzer
2   Willy   Jones
3   Rosy    Lily
4   Stuart  Littlt

df2:

    Name        First_Name
0   Braund      Owen
1   Heikkinen   Laina
2   Allen       William
3   Moran       James
4   McCarthy    Timothy

import itertools
from fuzzywuzzy import fuzz
p1 = list(itertools.product(*[df1['Name'].values, df2['Name'].values]))
p2 = list(itertools.product(*[df1['First_Name'].values, df2['First_Name'].values]))
for N1, N2 in zip(p1,p2):
    Name_ratio = fuzz.ratio(N1[0], N1[1])
    First_Name_ratio = fuzz.ratio(N2[0], N2[1])

You can like this way.

Upvotes: 1

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