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This tutorial will teach you how to clean text data in Python for textual analysis or sentiment analysis by vectorizing text data into a structured bag of words or tokens. The cleaning process involves removing numbers, symbols, and non-alphabetic characters, harmonizing letter case, and removing common stop words in a three-step process. Python simplifies this process, making it easy to transform raw text into a more structured format suitable for analysis. Let's see how this is done in a Jupyter notebook.