Lesson 12: Understand JSON/XML Parsers: If your source list is in a semi-structured format like JSON or XML, use dedicated parsers (e.g., Python’s json module, lxml for XML) rather than trying to parse with regex.
Lesson 13: Web Scraping Tools for Web-Based Lists: If the list is on a webpage, learn tools like BeautifulSoup or Scrapy to extract the HTML elements list to data containing your data before processing.
Think Beyond Simple Conversion:
Lesson 14: Consider Edge Cases and Scalability
What if the list grows very large? What if the format changes slightly in the future? Design your solution to be robust and scalable.
Lesson 15: Document Your Process: Especially for complex transformations, document the logic, assumptions made, and any cleaning steps. This is crucial for maintainability and collaboration.
By internalizing these 15 lessons, you’ll be well-equipped to tackle a wide range of “list to data” challenges and become highly proficient in data preparation.
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