[Python] How to clean a dataset for a chatbot while preserving code snippets and mathematical...

I’m working on a project where I need to clean a dataset that will be used for a chatbot. The dataset includes text data, code snippets, and mathematical formulas, and I want to ensure that while cleaning the data, I do not alter or break the code snippets or formulas.

Specifically, I want to:

Redact sensitive data such as URLs, email addresses, and personal information. Standardize dates and remove any unnecessary special characters from the non-code parts of the dataset. Preserve the integrity of code snippets and formulas by keeping the special characters, indentation, and syntax intact. My challenges are:

The dataset has columns that contain code snippets and mathematical formulas . Removing special characters or changing the formatting would make code snippets and formulas useless. What would be the best approach to clean this dataset while preserving the structure of the code and formulas? How should I:

Detect code snippets and formulas? Clean non-code text while leaving the code and formulas intact? Handle specific elements like LaTeX, Python code, or other syntaxes? Here’s the approach I’m considering:

Identify the code and formula sections using markers (e.g., backticks for code, LaTeX syntax for formulas). Clean only the non-code sections for personal data and irrelevant special characters. Avoid altering any syntax or formatting in the code or formulas. Any guidance, suggestions, or code examples on how to achieve this would be greatly appreciated!

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