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In this tutorial, we will learn how to clean text data on Python for textual or sentiment analysis. The process involves transforming raw text into a structured bag of words or tokens. Cleaning text involves three steps: removing numbers, symbols, and non-alphabetic characters, harmonizing letter case, and removing stop words. Python simplifies this process, making it easy to clean and prepare text data for analysis in Jupyter Notebook.