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#480: Ahoy, Narwhals are bridging the data science APIs
- 2024/10/09
- 再生時間： 59 分
- ポッドキャスト
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サマリー
あらすじ・解説
If you work in data science, you definitely know about data frame libraries. Pandas is certainly the most popular, but there are others such as cuDF, Modin, Polars, Dask, and more. They are all similar but definitely not the same APIs and Polars is quite different. But here's the problem. If you want to write a library that is for users of more than one of these data frame frameworks, how do you do that? Or if you want to leave open the possibility of changing yours after the app is built, same problem. That's the problem that Narwhals solves. We have Marco Gorelli on the show to tell us all about it.
Episode sponsors
WorkOS
Talk Python Courses
Links from the show
Marco Gorelli: @marcogorelli
Marco on LinkedIn: linkedin.com
Narwhals: github.io
Narwhals on Github: github.com
DuckDB: duckdb.org
Ibis: ibis-project.org
modin: readthedocs.io
Pandas and Beyond with Wes McKinney: talkpython.fm
Polars: A Lightning-fast DataFrame for Python: talkpython.fm
Polars: pola.rs
Pandas: pandas.pydata.org
Watch this episode on YouTube: youtube.com
Episode transcripts: talkpython.fm
--- Stay in touch with us ---
Subscribe to us on YouTube: youtube.com
Follow Talk Python on Mastodon: talkpython
Follow Michael on Mastodon: mkennedy
Episode sponsors
WorkOS
Talk Python Courses
Links from the show
Marco Gorelli: @marcogorelli
Marco on LinkedIn: linkedin.com
Narwhals: github.io
Narwhals on Github: github.com
DuckDB: duckdb.org
Ibis: ibis-project.org
modin: readthedocs.io
Pandas and Beyond with Wes McKinney: talkpython.fm
Polars: A Lightning-fast DataFrame for Python: talkpython.fm
Polars: pola.rs
Pandas: pandas.pydata.org
Watch this episode on YouTube: youtube.com
Episode transcripts: talkpython.fm
--- Stay in touch with us ---
Subscribe to us on YouTube: youtube.com
Follow Talk Python on Mastodon: talkpython
Follow Michael on Mastodon: mkennedy