Mar 12, 2022 · This tutorial explains how to perform fuzzy matching between two datasets in R, including an example.

Jul 23, 2025 · R offers several packages for fuzzy matching, including stringdist and fuzzyjoin. Here’s a detailed look at how to use these packages for fuzzy matching tasks.

Nov 6, 2025 · This guide will walk you through the core concepts and practical applications of fuzzy matching in R, equipping you with the skills to tackle real-world data challenges.

We will walk through how to effectively utilize the stringdist_join() function to execute robust fuzzy matching in R, ensuring that your data integration strategies are comprehensive and yield the …

After trying all the name cleaning that you can with clean_strings, you have gotten the ‘low hanging fruit’ of your match, and now you need to move on to non-exact matches. merge_plus has a built-in …

Nov 27, 2025 · In this blog, we’ll explore how to implement fuzzy matching in R to merge DataFrames containing student, father, and mother names, with a focus on fixing typos and reducing non-matches.

Here is a solution using the fuzzyjoin package. It uses dplyr -like syntax and stringdist as one of the possible types of fuzzy matching. As suggested by @C8H10N4O2, the stringdist method="jw" …

This tutorial provides several examples to help with fuzzy matching (also called fuzzy string searching or approximate string matching) in the R programming language.

This is used by fuzzy_match to perform a string distance-based match between two datasets. This process can take quite a long time, for quicker matches try adjusting the nthread argument in …

We'll start with a conceptual overview of fuzzy string matching, and then look at some examples in R using several different algorithms.