NumPy for Data Science | Why It’s Faster Than Python Lists + Core Concepts Explained

NumPy is the foundation of the Python Data Science Toolkit! 🚀
In this lecture, we cover:
• Why NumPy is faster than Python lists
• Memory optimization with arrays vs lists
• Array creation: arange, linspace, ones, zeros, eye, empty, fromfunction
• Attributes & reshaping: shape, ndim, dtype, reshape, transpose, ravel, flatten
• Arithmetic, comparison, and statistical operations (sum, mean, var, std, median)
• Special functions: log, exp, sin, cos, tan, ceil, floor
• Stacking, splitting, and practical examples

🎯 By the end, you’ll understand how NumPy powers modern Data Science and why it’s a must-learn tool.

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📘 Jupyter Notebook used:
https://drive.google.com/file/d/1O3I5X-qnUf-5KCMjbG5LxJaEOlzi0zlH/view?usp=drive_link

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Видео NumPy for Data Science | Why It’s Faster Than Python Lists + Core Concepts Explained канала Ajay Kumar Gupta