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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#510: 10 Polars Tools and Techniques To Level Up Your Data Science

Talk Python To Me