4.8 • 635 Ratings
🗓️ 9 October 2024
⏱️ 59 minutes
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0:00.0 | If you work in data science, you definitely know about data frame libraries. |
0:03.8 | Handis is certainly the most popular, but there are others such as QDF, Moden, Pollers, Dask, and more. |
0:10.9 | They're all similar, but definitely not the same APIs, and Pollers is quite different. |
0:15.3 | But here's the problem. |
0:16.5 | If you want to write a library that is for users of more than one of these data frame frameworks, |
0:21.7 | how do you do that? Or if you want to leave open the possibility of changing yours after the app is built, |
0:27.3 | you got the same problem. Well, that's what Narwhals solves. We have Marco Gorelli on the show to tell us |
0:33.3 | all about Narwhals. This is Talk Python to Me. Episode 480 recorded September 10th, |
0:39.6 | 2004. Are you ready for your host? Here you is. You're listening to Michael Kennedy on |
0:45.5 | Talk Python to Me. Life from Portland, Oregon, and this segment was made with Python. |
0:53.1 | Welcome to Talk Python, a weekly podcast on Python. This is your host, Michael Kennedy. |
0:58.9 | Follow me on Massadon, where I'm at M. Kennedy, and follow the podcast using at Talk Python, |
1:04.1 | both accounts over at Fostadon.org, and keep up with the show and listen to over nine years of episodes |
1:10.3 | at TalkPy python.fm. |
1:12.2 | If you want to be part of our live episodes, you can find the live streams over on YouTube, |
1:16.8 | subscribe to our YouTube channel over at talk python.fm slash YouTube and get notified about |
1:21.8 | upcoming shows. This episode is brought to you by WorkOS. If you're building a B2B SaaS app at some point, your customers will start asking for enterprise features like SAMA authentication, skim provisioning, audit logs, and fine-grained authorization. |
1:37.4 | WorkOS helps ship enterprise features on day one without slowing down your core product development. |
1:43.0 | Find out more at TalkP talk python.fm slash |
1:45.5 | workOS. |
1:47.1 | Marco, welcome to Talk Python. |
1:49.2 | Hi, thanks for having me. |
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