Handling Misspellings
Learn about misspellings, their causes, and how to handle them using Python.
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Introduction
Misspellings are typographical errors that occur when a word is not spelled correctly, and various factors, including typing errors, auto-correction software, and language barriers, can cause them. They can be found in social media posts, emails, online articles, blogs, etc. Even formal, official text sources, such as business documents and academic papers, can have misspellings, although finding such is rare.
Misspellings can cause confusion and ambiguity in written communication and affect the accuracy of text analysis and NLP. As such, it’s crucial to understand the impact of misspellings on text data and apply appropriate text preprocessing techniques to handle them. Let’s look at the various ways of handling misspellings in text data.
Spell-checking
Spell-checking is a valuable technique for handling misspellings, and it involves identifying and correcting misspelled words to improve the quality of the text data. Python offers several libraries for spell-checking, such as TextBlob and PySpellChecker. With the TextBlob library, we can perform spell-checking as shown in the code example below:
review_id,review_text,rating1,"I didn't lke the movie.",52,"The theatre was amazng!",43,"That was the worse movie I've ever seen.",54,"The custmer servce was terible.",25,"The snacks were delicios.",46,"I had a woderful experience at this hotel.",57,"The plot was horible.",38,"The performane of the actor was imprssive.",49,"The movie desription is inacurate.",2
Let’s review the code line ...