Comments on: 16 Top Python Hacks for Data Scientists to Improve Productivity

By: Kotesh

Kotesh — Thu, 06 Feb 2025 06:13:25 +0000

This is a fantastic collection of advanced Python tricks!

The tips on list comprehensions, generators, and defaultdict are especially useful for optimizing code efficiency. I also appreciate the inclusion of NumPy broadcasting and Scikit-learn pipelines, which are game-changers for data professionals.

Well-structured and informative—thanks for sharing these insights!

By: Ravi Saive

Ravi Saive — Mon, 03 Feb 2025 04:46:42 +0000

In reply to Jakob.

@Jakob,

Thanks for the feedback!

I’ll review and refine the approach for better optimization.

By: Jakob

Jakob — Sat, 01 Feb 2025 19:12:51 +0000

There are some nice tips in here, but it seems like you do what you suggest people not to, for memory and speed optimization. Generators are your best friend and you convert the ones returned my map and all the other by using "list()" so convert to a memory hungry format.