I am new to programming.I have a pandas data frame in which two string columns are present.
Data frame is like below:
Col-1 Col-2
Update have a account
Account account summary
AccountDTH Cancel
Balance Balance Summary
Credit Card Update credit card
Here i need to check the similarity of Col-2 elements with each element of Col-1.
It Means i have to compare have a account
with all the elements of Col-1
.
Then find the top 3 similar one. Suppose the similarity scores are :Account(85),AccountDTH(80),Balance(60),Update(45),Credit Card(35)
.
Expected Output is:
Col-2 Output
have a account Account(85),AccountDTH(80),Balance(60)
You can use a Python library like fuzzywuzzy
here, which has support for this type of task:
from fuzzywuzzy import process
df.assign(Output=[process.extract(i, df['Col-1'], limit=3) for i in df['Col-2']])
Using the process
method, we can get string similary scores, and then pick the top 3, if 3 exist:
The output of the above code:
Col-1 Col-2 Output
0 Update have a account [(Account, 90, 1), (AccountDTH, 64, 2), (Update, 40, 0)]
1 Account account summary [(Account, 90, 1), (AccountDTH, 63, 2), (Credit Card, 38, 4)]
2 AccountDTH Cancel [(Balance, 62, 3), (Credit Card, 43, 4), (Update, 33, 0)]
3 Balance Balance Summary [(Balance, 90, 3), (Credit Card, 38, 4), (Update, 30, 0)]
4 Credit Card Update credit card [(Update, 90, 0), (Credit Card, 90, 4), (AccountDTH, 27, 2)]
To speed this comparison up (natively it uses Python's sequence matcher), I would recommend installing python-Levenshtein