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in this video were going to learn how to clean text data on python just a quick recap though recall that we said cleaning text data essentially involves transforming raw text into a format thats suitable for textual analysis or indeed sentiment analysis and we said that formally it essentially involves vectorizing text data i going from a blob of text to a somewhat relatively more structured bag of words or a list of words or tokens of words further recall that we said cleaning text is a sort of three-step process where we start by removing numbers symbols and all non-alphabetic characters then move on to harmonizing the letter k so for instance ensuring that all words are lowercase and finally removing the most common words i removing stop words now thankfully python makes this entire process incredibly easy so lets go ahead and see what this looks like in our jupyter notebook so here we are in a brand new jupyter notebook and the first thing youll notice of course is that there