What are the best practices for debugging in data science?
Some best practices include using version control, writing tests, and logging your code execution.
Can you explain why version control is important?
Version control helps track changes, collaborate with others, and revert to previous states if a bug is introduced.
What tools do you recommend for logging?
Popular logging tools include Python's logging module, Loguru, and third-party services like Sentry.
How can I effectively test my data processing functions?
You can use unit tests with frameworks like pytest to ensure your functions handle various inputs correctly.
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