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.
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Wow, what a great podcast!This is currently one of my favorite podcasts. It's intelligent, informative, and is a treasure of not just Python programming, but programming in general. Keep up the good work! Thanks.
InterestingNot a how-to but addictively fascinating. It is neat to see how people are using Python.
Required listeningVery substantive, polished podcast. Michael is the ideal interviewer: deeply knowledgeable and prepared, but knows how to get out of the way and let his guests dominate the conversation. Absolutely required listening for all Pythoneers IMO.
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