[Python] Roadmap and Resources for Live Coding Interview in Python (Data Science) [closed]

I have an upcoming interview where the next round will be live coding in Python. I will be given a dataset and expected to perform data science tasks on it. Could anyone suggest a roadmap or preparation plan for tackling such interviews? Also, any specific resources that could help would be appreciated.

To provide more context:

I'm comfortable with Python and have experience with libraries like pandas, NumPy, and scikit-learn. I have a good grasp of data preprocessing, feature engineering, and basic machine learning models. I have worked on projects involving both structured and unstructured data. I'm looking for advice on:

1. Key areas to focus on before the interview (e.g., specific algorithms, handling missing data, etc.).
2. Best practices during live coding (e.g., time management, how to explain your thought process).
3. Recommended resources or practice problems for honing these skills under interview conditions.

Thanks in advance for the help!

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