We are making an algorithom using python.we have unsorted and mispelled country names in google spreadsheet. we will use levenshtein algorithom so that we can have a correct set of data where all country names are reasonably correct and summarized as one country and respective count
####Metaphone [Metaphone] (https://en.wikipedia.org/wiki/Metaphone#Metaphone_3) is a phonetic algorithm, published by Lawrence Philips in 1990, for indexing words by their English pronunciation.[1] It fundamentally improves on the Soundex algorithm by using information about variations and inconsistencies in English spelling and pronunciation to produce a more accurate encoding, which does a better job of matching words and names which sound similar. As with Soundex, similar-sounding words should share the same keys. Metaphone is available as a built-in operator in a number of systems.
The original author later produced a new version of the algorithm, which he named Double Metaphone. Contrary to the original algorithm whose application is limited to English only, this version takes into account spelling peculiarities of a number of other languages. In 2009 Lawrence Philips released a third version, called Metaphone 3, which achieves an accuracy of approximately 99% for English words, non-English words familiar to Americans, and first names and family names commonly found in the United States, having been developed according to modern engineering standards against a test harness of prepared correct encodings.
####Levenshtein distance In information theory, linguistics and computer science, the Levenshtein distance is a string metric for measuring the difference between two sequences. Informally, the Levenshtein distance between two words is the minimum number of single-character edits (insertions, deletions or substitutions) required to change one word into the other. It is named after the Soviet mathematician Vladimir Levenshtein, who considered this distance in 1965.
python v3
Gspread
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