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This video tutorial teaches how to clean text data in Python for textual analysis and sentiment analysis. Cleaning text involves transforming raw text into a structured bag of words or list of tokens through vectorization. The process includes removing numbers, symbols, non-alphabetic characters, harmonizing letter casing, and removing stop words. Python simplifies this process and makes it easy in Jupyter Notebook.