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Python is not a great language for data science

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Re: Python is not a great language for data science

#171

Post by dreamcompiler »

iLemming wrote: post #139
MarsIronPI wrote: post #107

Earlier quoted context omitted.

Common Lisp fan here, but not a data scientist. Why do you say to avoid CL for data analysis? Not trying to flame or anything, just curious about your experience with it.

I don't have great experience of using CL for analyzing data, because of "why?", if I already have another Lisp that is simply amazing for data. Clojure, unlike lists in traditional Lisps, based on composable, unified abstraction for its collections, they are lazy by default and literal readable data structures, they are far easier to introspect and not so "opaque" compared to anything - not just CL (even Python), th…

Homework assignments notwithstanding, very few serious Common Lisp programs use lists and symbols as their primary data structures. This has been true since around 1985.

Common Lisp has O[1] vectors, multidimensional arrays, hash-tables (what Clojure calls maps), structs, and objects. It has set operations too but it doesn't enforce membership uniqueness. It also has bignums, several sizes of floats, infinite-precision rationals, and complex numbers. Not to mention characters, strings, and logical operations on individual bits. The main difference from Clojure is that CL data structures are not immutable. But that's an orthogonal issue to the suggestion that CL doesn't contain a rich library of modern data structures.

Common Lisp has never been limited to "List Processing."

Re: Python is not a great language for data science

#175

Post by evolighting »

_yb2s wrote: post #146
evolighting wrote: post #140

Earlier quoted context omitted.

R is more of a statistical software than a programming language. So, if you are a so-called "statistician," then R will feel familiar to you

No, R is a serious general purpose programming language that is great for building almost any type of complex scientific software with. Projects like Bioconductor are a good example.

Perhaps a in a context of comparison with Python?

In my limited experience, Using R feels like to using JavaScript in the browser: it's a platform heavily focused on advanced, feature-rich objects (such as DataFrames and specialized plot objects). but you could also just build almost anything with it.

Re: Python is not a great language for data science

#176

Post by culebron21 »

This was underwhelming. I work with Python and Pandas, and I can show examples of much clumsier workflows I run into. The most often, you get dataframe[(dataframe.column1 == something) & ~dataframe.column2.isna()] constucts, which show that python syntax falls short here, and isn't suitable for such manipulations. Unfortunately, there's no alternative, and I don't see R as much easier, there are plenty of ugly things as well there.

There's Julia -- it has serious drawbacks, like slow cold start if you launch a Julia script from the shell, which makes it unsuitable for CLI workflows.

Otherwise you have to switch to compiled languages, with their tradeoffs.

Re: Python is not a great language for data science

#177

Post by pphysch »

kelipso wrote: post #170
pphysch wrote: post #128

Earlier quoted context omitted.

Deeply ironic for a Julia proponent to smear a popular language as "fundamentally broken" without evidence. https://yuri.is/not-julia/

This is like one of those people posting Dijkstra’s letter advocating for 0-based indexing without ever having read or understood what they posted.

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

Re: Python is not a great language for data science

#178

Post by theamk »

lock1 wrote: post #155
OkayPhysicist wrote: post #130

Earlier quoted context omitted.

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…

That's needlessly aggressive. Ignoring webapps, you could do gamedev without even knowing what a matrix is. You don't even need such construction in most native applications, embedded systems, and OS kernel development.

I am working in embedded. Had to optimize weights for an embedded algorithm, decided to use linear regression and thus needed matrices.

And if you do robotics, the chances of encountering a matrix are very high.

Re: Python is not a great language for data science

#179

Post by throwaway2037 »

lock1 wrote: post #155
OkayPhysicist wrote: post #130

Earlier quoted context omitted.

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…

That's needlessly aggressive. Ignoring webapps, you could do gamedev without even knowing what a matrix is. You don't even need such construction in most native applications, embedded systems, and OS kernel development.

This is my exactly point. Even in a highly specialised library for pricing securities, the amount of code that uses matrices is surprisingly small.
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