Fuzzy String Matching in Python: Clean Data, Find Duplicates, and Save Hours

Learn how to use Python and FuzzyWuzzy to clean messy data, fix typos, find duplicates, and automate string matching with just a few lines of code.

Working with messy data can be a real pain—especially when names are spelled differently, formats are all over the place, or there are just plain typos. That’s where a Python library called FuzzyWuzzy comes in handy.

It’s made to help you compare words and phrases that aren’t exactly the same, but close enough to match. Behind the scenes, it uses something called the Levenshtein Distance to figure out how similar two strings are.

So why use FuzzyWuzzy? Think of it like a helpful spell-checker for your data—it doesn’t care if things are messy, it just helps you find what you’re looking for.

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FuzzyWuzzy makes it way easier to match things up that obviously belong together but don’t look the same at first glance.

Oh, and honestly, it only takes a couple lines of code to get it working. That’s what makes it so useful—you don’t need to build anything complicated to start getting good results.

In this article, I’ll walk you through how to use FuzzyWuzzy to compare strings, match items in lists, and even clean up messy data automatically. Maybe you’re building a recommendation tool, cleaning up product titles from different sources, or just trying to get two lists to line up, this library can save you a ton of time.

Let’s start by installing it. Open up your terminal and run:

pip install fuzzywuzzy 
pip install python-Levenshtein # (optional but speeds things up!)

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Now you’re all set—those messy strings don’t stand a chance.

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