Why I Switched From Pandas to Polars | TDE Workshop

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​In this workshop, Ben breaks down the 3 reasons he has permanently switched from Pandas to Polars and goes through a demo with code.

Led by: Ben Feifke

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Overview - 0:00
About Ben - 0:29
What's Polars - 3:19
Reason 1: .list namespace - 5:30
Reason 2: .scan_parquet() and .sink_parquet() - 11:48
Reason 3: Data-oriented Programming - 16:16
Demo - 20:58
Some Questions - 34:52
What’s Next? - 36:48
Q&A - 39:00
  1. The Data Entrepreneurs
  2. data science
  3. pandas
  4. polars
  5. python code
  6. python
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Комментарии
Автор

Although I see the benefits of Polars. I haven't had enough obstacle with Pandas for my workflows. I don't deal datasets that exceed memory and I think currently I can extend my memory limit using Dask ... but looking forward to the development of Polars and will likely adopt once it has more support!

spikeydude
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It is a shame that the lazy API is so entangled into the API. Might be nice to write generic code which then has the option to switch on the lazy API with one single change. I don't like the idea of having to rewrite the whole codebase to switch between lazy and eager. I question if that was a good design decision from polars. - Side note please always upload videos in 1080p

smellypunks
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man, we can read.
why read everything on the screen?

yjmfdkb
Автор

Pandas is a massive mess. It's very easy to write very poor code in Pandas but to write it well is not that intuitive, Matt Harrison has written some great stuff, but it's not that easy to learn.

Polars is way better and improving all the time. It's much easier to write and way quicker. The lazy API is a thing of beauty.

DarrenSaw