Python Bytes is a weekly podcast hosted by Michael Kennedy and Brian Okken. The show is a short discussion on the headlines and noteworthy news in the Python, developer, and data science space.
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محتوای ارائه شده توسط Michael Kennedy. تمام محتوای پادکست شامل قسمتها، گرافیکها و توضیحات پادکست مستقیماً توسط Michael Kennedy یا شریک پلتفرم پادکست آنها آپلود و ارائه میشوند. اگر فکر میکنید شخصی بدون اجازه شما از اثر دارای حق نسخهبرداری شما استفاده میکند، میتوانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal
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#480: Ahoy, Narwhals are bridging the data science APIs
Manage episode 444393209 series 2453836
محتوای ارائه شده توسط Michael Kennedy. تمام محتوای پادکست شامل قسمتها، گرافیکها و توضیحات پادکست مستقیماً توسط Michael Kennedy یا شریک پلتفرم پادکست آنها آپلود و ارائه میشوند. اگر فکر میکنید شخصی بدون اجازه شما از اثر دارای حق نسخهبرداری شما استفاده میکند، میتوانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal
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
…
continue reading
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 Talk Python on YouTube: youtube.com
Talk Python on Bluesky: @talkpython.fm at bsky.app
Talk Python on Mastodon: talkpython
Michael on Bluesky: @mkennedy.codes at bsky.app
Michael on Mastodon: mkennedy
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 Talk Python on YouTube: youtube.com
Talk Python on Bluesky: @talkpython.fm at bsky.app
Talk Python on Mastodon: talkpython
Michael on Bluesky: @mkennedy.codes at bsky.app
Michael on Mastodon: mkennedy
508 قسمت
Manage episode 444393209 series 2453836
محتوای ارائه شده توسط Michael Kennedy. تمام محتوای پادکست شامل قسمتها، گرافیکها و توضیحات پادکست مستقیماً توسط Michael Kennedy یا شریک پلتفرم پادکست آنها آپلود و ارائه میشوند. اگر فکر میکنید شخصی بدون اجازه شما از اثر دارای حق نسخهبرداری شما استفاده میکند، میتوانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal
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
…
continue reading
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 Talk Python on YouTube: youtube.com
Talk Python on Bluesky: @talkpython.fm at bsky.app
Talk Python on Mastodon: talkpython
Michael on Bluesky: @mkennedy.codes at bsky.app
Michael on Mastodon: mkennedy
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 Talk Python on YouTube: youtube.com
Talk Python on Bluesky: @talkpython.fm at bsky.app
Talk Python on Mastodon: talkpython
Michael on Bluesky: @mkennedy.codes at bsky.app
Michael on Mastodon: mkennedy
508 قسمت
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