fuzzywuzzy

I am learning fuzzywuzzy in Python. I understand the concept of fuzz.ratio , fuzz.partial_ratio , fuzz.token_sort_ratio and fuzz.token_set_ratio . My question is when to use which function? Do I check the 2 strings' length first, say if not similar, then rule out fuzz.partial_ratio ? If the 2 strings' length are similar, I'll use fuzz.token_sort_ratio ? Should I always use fuzz.token_set_ratio ? Anyone knows what criteria SeatGeek uses? I am trying to build a real estate website, thinking to use fuzzywuzzy to compare addresses. Rick Hanlon II Great question. I'm an engineer at SeatGeek, so I

I have the following problem I have a dataframe master that contains sentences, such as master Out[8]: original 0 this is a nice sentence 1 this is another one 2 stackoverflow is nice For every row in Master, I lookup into another Dataframe slave for the best match using fuzzywuzzy . I use fuzzywuzzy because the matched sentences between the two dataframes could differ a bit (extra characters, etc). For instance, slave could be slave Out[10]: my_value name 0 2 hello world 1 1 congratulations 2 2 this is a nice sentence 3 3 this is another one 4 1 stackoverflow is nice Here is a fully

I have two data frames with each having a different number of rows. Below is a couple rows from each data set df1 = Company City State ZIP FREDDIE LEES AMERICAN GOURMET SAUCE St. Louis MO 63101 CITYARCHRIVER 2015 FOUNDATION St. Louis MO 63102 GLAXOSMITHKLINE CONSUMER HEALTHCARE St. Louis MO 63102 LACKEY SHEET METAL St. Louis MO 63102 and df2 = FDA Company FDA City FDA State FDA ZIP LACKEY SHEET METAL St. Louis MO 63102 PRIMUS STERILIZER COMPANY LLC Great Bend KS 67530 HELGET GAS PRODUCTS INC Omaha NE 68127 ORTHOQUEST LLC La Vista NE 68128 I joined them side by side using combined_data = pandas