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Python is not a great language for data science

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281–290 of 339 posts

Re: Python is not a great language for data science

#281

It’s not. Julia is better, much better. But Julia came too late. A lot of data science code is already in Python. That’s where it’s going to stay because rewriting code is time consuming. My guess is we will continue to improve Python gradually and keep refactoring the code.

Julia macros are a game changers.

You do not need a DSL.

Re: Python is not a great language for data science

#282
post #16

I think a lot of this comes down to the question: Why aren't tables first class citizens in programming languages? If you step back, it's kind of weird that there's no mainstream programming language that has tables as first class citizens. Instead, we're stuck learning multiple APIs (polars, pandas) which are effectively programming languages for tables. R is perhaps the closest, because it has data.frame as a 'firs…

Mathematica recently added the Tabular command, for what it’s worth. I haven’t used it much yet, but it seems to be quite capable.

Re: Python is not a great language for data science

#283
post #223
post #185

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These days it’s still a whole lot of Fortran, with some Rust sprinkled on top. (:

Which since Fortran 2003, or even Fortran 95, has gotten rather nice to use.

IDK it's become too verbose IMHO, looks almost like COBOL now. (I think it was Fortran 66 that was the last Fortran true to its nature as a "Formula Translator"...)

Re: Python is not a great language for data science

#284

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> There's a number of structures that I think are missing in our major programming languages. Tables are one. Matrices are another. I disagree. Most programmers will go their entire career and never need a matrix data structure. Sure, they will use libraries that use matrices, but never use them directly themselves. It seems fine that matrices are not a separate data type in most modern programming languages.

Unless you think "most programmers" === "shitty webapp developers", I strongly disagree. Matrices are first class, important components in statistics, data analysis, graphics, video games, scientific computing, simulation, artificial intelligence and so, so much more. And all of those programmers are either using specialized languages, (suffering problems when they want to turn their program into a shitty web app, fo…

At least in C++ you don't need 'matmul'

Re: Python is not a great language for data science

#285
post #223

Earlier quoted context omitted.

Which since Fortran 2003, or even Fortran 95, has gotten rather nice to use.

IDK it's become too verbose IMHO, looks almost like COBOL now. (I think it was Fortran 66 that was the last Fortran true to its nature as a "Formula Translator"...)

We are way beyond comparing languages to COBOL, now that plenty folks type whole book sized descriptions into tiny chat windows for their AI overloads.

Re: Python is not a great language for data science

#286

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"The reason you can use this simpler syntax in R is because it’s non-standard-evaluation ..." So it actually is about Python vs R. That said, while this kind of non-standard evaluation is nice when working interactively on the command line, I don't think it's that relevant when writing code for more elaborated analyses. In that context, I'd actually see this as a disadvantage of R because you suddenly have to jump th…

The increasing prevalence of non-standard evaluation in R packages was one of the major reasons I switched from R to python for my work. The amount of ceremony and constant API changes just to have something as an argument in a function drove me mad.

> nd constant API changes

Yeah, this was so very very painful. I once ended up maintaining a library that basically used all the different NSE approaches, which was not very much fun at all.

Re: Python is not a great language for data science

#287
post #218

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The bloated standard library is the only reason I kept using python in spite of the packaging nightmare. I can do most things with no dependencies, or with one dependency I need over and over like matplotlib If python had been lean and needed packages to do anything useful, while still having a packaging nightmare, it would have been unusable

Well, sure, but equally I think there would have been a lot more effort to fix the packaging nightmare if it had been more urgent.

There was a massive effort though, the proliferation of several different package managers is evidence of that.

Re: Python is not a great language for data science

#288

Earlier quoted context omitted.

What does indexing syntax have to do with Julia having a rough history of correctness bugs and footguns?

Sure, all software is terrible if looking at bug frequency history... https://github.com/python/cpython/issues Griefers ranting about years old _closed_ tickets on v1.0.5 versions on a blog as some sort of proof of lameness... is a poorly structured argument. Julia includes regression testing features built into even its plotting library output, and thus issues usually stay resolved due to pedantic reproducibility. A…

Just saying, "other languages have bug reports" is a exceptionally poor way to promote Julia =3

Re: Python is not a great language for data science

#290
post #183

Earlier quoted context omitted.

> R failed to evolve, let's be honest. Python won via jupyter Ju = Julia Pyt = Python Er = R R is not only supported in Jupyter, it was there from the start. I’ve never written a single line of R. It is bizarre how little people know about their tools.

But it used to be iPython (and the notebook interface did come out when it was still iPython).

Yeah. The extra language support is partially why they renamed it.
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