Enhance cleaning.py with docstrings, safety checks, unit tests, and demo notebook

[Sudharshika]

✨ Highlights

• Expanded and professional docstrings for cleaning.py functions (parameters, returns, examples).
• Added defensive programming: input validation in rename_columns_auto.
• Improved docstrings for replace_specials and verified with manual tests.
• Added unit tests for missing_summary, outlier_summary, and fill_missing.
• Verified all tests pass with pytest -v.
• Created a beginner‑friendly Jupyter notebook demo (demo_cleaning.ipynb) showcasing the cleaning workflow on Titanic dataset.

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This PR improves the usability, robustness, and beginner‑friendliness of the cleaning.py module by adding:

• Docstring Enhancements

  • Expanded rename_columns_auto docstring with parameters, return type, and example usage.
  • Improved docstrings for replace_specials and other functions for clarity and consistency.

• Defensive Programming (Safety Checks)

  • Added input validation to rename_columns_auto:

    if not isinstance(df, pd.DataFrame):
        raise TypeError("Input must be a pandas DataFrame")

  • Prevents silent bugs and enforces correct usage.

• Unit Tests

  • Added tests for missing_summary, outlier_summary, and fill_missing.
  • Verified correctness with pytest (pytest -v → all tests passed).

• Manual Testing

  • Ran quick manual tests for replace_specials and confirmed expected behavior.

• Demo Notebook (demo_cleaning.ipynb)

  • Beginner‑friendly walkthrough of cleaning workflow on Titanic dataset.
  • Demonstrates column renaming, missing value handling, outlier detection/removal, and text cleaning.
  • Includes Markdown explanations and a conclusion for clarity.

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✅ Value Added

• Clearer documentation for maintainers and contributors.
• Safer, more robust functions with input validation.
• Verified correctness through automated and manual tests.
• Beginner‑friendly demo notebook for onboarding and reproducibility.

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🔧 Checklist

• Docstrings updated
• Input validation added
• Unit tests created and passing
• Manual tests verified
• Demo notebook created and tested

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📂 Suggested Placement

• Tests located in tests/test_cleaning.py
• Demo notebook located in demos/demo_cleaning.ipynb

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