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Pandas and Polars with Marco Gorelli

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Manage episode 379375625 series 2836526
内容由Nicola Corti提供。所有播客内容(包括剧集、图形和播客描述)均由 Nicola Corti 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

Time for a brand-new topic today here at The Developers’ Bakery: Data Science! We’re really excited to have on stage Marco Gorelli, core contributor of both pandas and polars, two of the most popular data science libraries in the Python ecosystem.

In this episode, we’ll talk about how pandas became so popular in the data science space. Then we’ll move on to talk about polars, a new data science library written in Rust, and how its performances compare to pandas.

Finally, we’ll have the opportunity to touch on a very interesting and unique topic: the Dataframe Consortium, a multi-company effort to standardize the data science API across the ecosystem.

Enjoy the show 👨‍🍳

Show Notes

  • 00.14 Intro
  • 01.00 Episode Start
  • 01.30 Marco’s Introduction
  • 02.14 What is pandas?
  • 03.27 Why do I need pandas?
  • 05.19 pandas’ competitors
  • 07.24 pandas’ popularity
  • 10.12 What’s your role with pandas?
  • 12.39 How to become a pandas maintainer?
  • 13.50 From data scientist to open source maintainer
  • 16.02 What is polars?
  • 21.22 Can pandas and polars co-exist?
  • 24.25 Performance benchmarks
  • 26.21 The learning curve
  • 29.11 Naming anecdotes
  • 30.51 The Dataframe Consortium?
  • 40.12 Marco’s role in the consortium
  • 43.40 What’s next for polars?
  • 46.50 How to start contributing?
  • 50.56 Further reading
  • 53.33 Where people can find you online?

Resources

Show links

  continue reading

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Artwork
icon分享
 
Manage episode 379375625 series 2836526
内容由Nicola Corti提供。所有播客内容(包括剧集、图形和播客描述)均由 Nicola Corti 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

Time for a brand-new topic today here at The Developers’ Bakery: Data Science! We’re really excited to have on stage Marco Gorelli, core contributor of both pandas and polars, two of the most popular data science libraries in the Python ecosystem.

In this episode, we’ll talk about how pandas became so popular in the data science space. Then we’ll move on to talk about polars, a new data science library written in Rust, and how its performances compare to pandas.

Finally, we’ll have the opportunity to touch on a very interesting and unique topic: the Dataframe Consortium, a multi-company effort to standardize the data science API across the ecosystem.

Enjoy the show 👨‍🍳

Show Notes

  • 00.14 Intro
  • 01.00 Episode Start
  • 01.30 Marco’s Introduction
  • 02.14 What is pandas?
  • 03.27 Why do I need pandas?
  • 05.19 pandas’ competitors
  • 07.24 pandas’ popularity
  • 10.12 What’s your role with pandas?
  • 12.39 How to become a pandas maintainer?
  • 13.50 From data scientist to open source maintainer
  • 16.02 What is polars?
  • 21.22 Can pandas and polars co-exist?
  • 24.25 Performance benchmarks
  • 26.21 The learning curve
  • 29.11 Naming anecdotes
  • 30.51 The Dataframe Consortium?
  • 40.12 Marco’s role in the consortium
  • 43.40 What’s next for polars?
  • 46.50 How to start contributing?
  • 50.56 Further reading
  • 53.33 Where people can find you online?

Resources

Show links

  continue reading

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