Giles Weaver & Ian Ozsvald - Pandas 2, Dask or Polars? Tackling larger data on a single machine

Pandas 2 brings new Arrow data types, faster calculations and better scalability. Dask scales Pandas across cores. Polars is a new competitor to Pandas designed around Arrow with native multicore support. Which should you choose for modern research workflows? We'll solve a "just about fits in ram" data task using the 3 solutions, talking about the pros and cons so you can make the best choice for your research workflow. You'll leave with a clear idea of whether Pandas 2, Dask or Polars is the tool for your team to invest in.

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00:00 Welcome!
00:10 Help us add time stamps or captions to this video! See the description for details.

[AadidevSooknananNXS]

This is possibly the best (worst) way to make a technical talk exciting, literally burst into flames!

[JOHNSMITH-verq]

Why’d it end suddenly?? Very weird stuff.

[pietraderdetective]

Did the speaker intentionally used .query() ?
It is one of the slowest method in Pandas.

[imtryinghere]

Crappy talk. Limited information. Tons of extraneous nonsense. Nothing on dask

[ringpolitiet]

While having a baby is a big thing in the parents' life, it has no relevance to PyData.