I pull data out of an RDBMS. And then put it into an RDBMS-like structure with weaker algebra and inferred types? That feels wrong.
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What I want to do is apply functional transformations to the data at that point. Instead I get a bespoke version of SQL grammar.
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And because of the way it handles types, chaining transformations means I'm going to jail for 4 felony counts of breaking the Law of Demeter
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If a monad is a burrito, pandas is a burrito bowl. Preferable to some, but not my style.
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I get that this was designed for academics who want the straightforwardness. But I find it frustrating given my software eng background.
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I'd just write SQL if I wanted SQL.
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I guess pandas is a stat program or something but since I dont know it I'm just going to assume you're talking about pandas w calculators
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I'm not sure I'm not
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I totally didn't follow the rest of the thread except I think you're saying the pandas enjoy burrito bowls and you'd make a different choice
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This is datasci in a nutshell
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Idk but now I want a burrito bowl, so thanks for that What is Odds ratio for burrito-bowl acquisition
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Pandas takes some getting used to, but it's really not like SQL at all.
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It's all about split-apply-combine. Vectorized operations are wildly much faster than iterating.
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I am fully aware of all of these things.
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I wrote finite element code in python 14 years ago. I'm fully cognizant of the design of the language and the tool.
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I thought you were talking about actual pandas for a sec and my reaction was way too dramatic.
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i thought you were talking about actual, animal panda bears and thought you were either confused, or now a markov bot
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They're super lazy and like not even trying to camouflage. Anybody?
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