Are you using Polars for your data science work? Maybe you've been sticking with the tried-and-true Pandas? There are many benefits to Polars directly of course. But you might not be aware of all the excellent tools and libraries that make Polars even better. Examples include Patito which combines Pydantic and Polars for data validation and polars_encryption which adds AES encryption to selected columns. We have Christopher Trudeau back on Talk Python To Me to tell us about his list of excellent libraries to power up your Polars game and we also talk a bit about his new Polars course.


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Links from the show

New Theme Song (Full-Length Download and backstory): talkpython.fm/blog


Polars for Power Users Course: training.talkpython.fm

Awesome Polars: github.com

Polars Visualization with Plotly: docs.pola.rs

Dataframely: github.com

Patito: github.com

polars_iptools: github.com

polars-fuzzy-match: github.com

Nucleo Fuzzy Matcher: github.com

polars-strsim: github.com

polars_encryption: github.com

polars-xdt: github.com

polars_ols: github.com

Least Mean Squares Filter in Signal Processing: www.geeksforgeeks.org

polars-pairing: github.com

Pairing Function: en.wikipedia.org

polars_list_utils: github.com

Harley Schema Helpers: tomburdge.github.io

Marimo Reactive Notebooks Episode: talkpython.fm

Marimo: marimo.io

Ahoy Narwhals Podcast Episode Links: talkpython.fm

Watch this episode on YouTube: youtube.com

Episode #510 deep-dive: talkpython.fm/510

Episode transcripts: talkpython.fm


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Talk Python To Me

10 Polars Tools and Techniques To Level Up Your Data Science

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