This checklist covers the essentials of NumPy in one place, helping you:

- Create and initialize arrays
- Perform element-wise computations
- Stack and split arrays
- Apply linear algebra functions
- Efficiently index, slice, and manipulate arrays

…and much more!

Feel free to share if you found this useful, and let me know in the comments if I missed anything!

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🐼 "Comparison Between SQL and pandas" – A Handy Reference Guide

⚡️ As a data scientist, I often found myself switching back and forth between SQL and pandas during technical interviews. I was confident answering questions in SQL but sometimes struggled to translate the same logic into pandas – and vice versa.

🔸 To bridge this gap, I created a concise booklet in the form of a comparison table. It maps SQL queries directly to their equivalent pandas implementations, making it easy to understand and switch between both tools.

⚡ This reference guide has become an essential part of my interview prep. Before any interview, I quickly review it to ensure I’m ready to tackle data manipulation tasks using either SQL or pandas, depending on what’s required.

📕 Whether you're preparing for interviews or just want to solidify your understanding of both tools, this comparison guide is a great way to stay sharp and efficient.

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