fuzzy-search

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

I'm looking for a fuzzy search JavaScript library to filter an array. I've tried using fuzzyset.js and fuse.js , but the results are terrible (there are demos you can try on the linked pages). After doing some reading on Levenshtein distance, it strikes me as a poor approximation of what users are looking for when they type. For those who don't know, the system calculates how many insertions , deletions , and substitutions are needed to make two strings match. One obvious flaw, which is fixed in the Levenshtein-Demerau model, is that both blub and boob are considered equally similar to bulb

I've been working on a way to join two datasets based on a imperfect string, such as a name of a company. In the past I had to match two very dirty lists, one list had names and financial information, another list had names and address. Neither had unique IDs to match on! ASSUME THAT CLEANING HAS ALREADY BEEN APPLIED AND THERE MAYBE TYPOS AND INSERTIONS. So far AGREP is the closest tool I've found that might work. I can use levenshtein distances in the AGREP package, which measure the number of deletions, insertions and substitutions between two strings. AGREP will return the string with the

DESCRIPTION I have two datasets with information that I need to merge. The only common fields that I have are strings that do not perfectly match and a numerical field that can be substantially different The only way to explain the problem is to show you the data. Here is a.csv and b.csv . I am trying to merge B to A. There are three fields in B and four in A. Company Name (File A Only), Fund Name, Asset Class, and Assets. So far, my focus has been on attempting to match the Fund Names by replacing words or parts of the strings to create exact matches and then using: a <- read.table(file =