Flookup is an advanced fuzzy matching and lookup add-on for Google Sheets. It adds functions to your spreadsheet for comparing any two strings based on percentage similarity and also searching tables based on percentage or sound similarity.
You can also use Flookup to highlight cells or delete rows with duplicate values based on percentage or sound similarity.
Flookup features a completely flexible and familiar syntax, a robust fuzzy matching algorithm and multi-directional lookup capabilities— all of which make Flookup fast, accurate and reliable.
GETTING STARTED WITH FLOOKUP
- Get Flookup from the G Suite Marketplace or the Chrome Web Store.
- Once installed, access the functions by either typing
=RDwithin any cell of your Google spreadsheet. You can also highlight cells or delete rows with duplicate values by accessing the respective functions through the add-on menu.
- Visit the tutorial page to learn how to use the add-on.
- Visit the changelog and the notices page to keep up-to-date with important changes to Flookup.
ABOUT Fuzzy Matching
Fuzzy matching (also called partial matching or approximate matching) is a technique for comparing strings that might have a less than 100% match. There are different techniques that are applied by fuzzy matching algorithms and the most popular involve the use of wildcard characters, word or phrase comparisons, regular expressions and edit distance. Examples include:
- Levenshtein Distance: This algorithm calculates and returns the minimum number of single-character edits (i.e. insertions, deletions or substitutions) required to change one word into another.
- Damerau–Levenshtein Distance: This algorithm is exactly like Levenshtein distance with one exception; it includes transpositions amongst its edits.
- Jaro–Winkler Distance: The Jaro distance between two words is the minimum number of single-character transpositions required to change one word into the other.
- n-gram: This is a contiguous sequence of n items from a given sequence of text or speech. The items can be phonemes, syllables, letters, words or base pairs according to the application.
- Soundex: This is a phonetic algorithm for indexing names by sound, as pronounced in English. The goal is for homophones to be encoded to the same representation so that they can be matched despite minor differences in spelling.
- The Brain: "Aoccdrnig to a rscheearch at Cmabrigde Uinervtisy, it deosn't mttaer in waht oredr the ltteers in a wrod are, the olny iprmoatnt tihng is taht the frist and lsat ltteers be at the rghit pclae. The rset can be a toatl mses and you can sitll raed it wouthit porbelm. Tihs is bcuseae the huamn mnid deos not raed ervey lteter by istlef, but the wrod as a wlohe."