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This video tutorial demonstrates how to clean text data using Python for textual or sentiment analysis. The process involves transforming raw text into a structured format by removing numbers, symbols, and non-alphabetic characters, harmonizing letter casing, and removing stop words. Python simplifies this three-step process by easily converting text data into a bag of words or a list of tokens. In a Jupyter notebook, the speaker will show how to perform text cleaning efficiently.