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

- Create and initialize arrays
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- 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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Loading CSV files into a database using Python.

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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.

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📕 Mastering NumPy – From Basics to Advanced

NumPy is an essential library in the world of data science, widely recognized for its efficiency in numerical computations and data manipulation. This powerful tool simplifies complex operations with arrays, offering a faster and cleaner alternative to traditional Python lists and loops.

The "Mastering NumPy" booklet provides a comprehensive walkthrough—from array creation and indexing to mathematical/statistical operations and advanced topics like reshaping and stacking. All concepts are illustrated with clear, beginner-friendly examples, making it ideal for anyone aiming to boost their data handling skills.

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📖 A comprehensive cheat sheet for working with Polars


🌟 Have you ever worked with pandas and thought that was the fastest way? I thought the same thing until I worked with Polars.

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🥇 40+ Real and Free Data Science Projects

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New to Pandas?

Here's a cheat sheet you can download (2025)

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