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JavaScript for Data Science

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Re: JavaScript for Data Science

#21

Post by brylie »

brylie wrote: post #20
slver wrote: post #13

Earlier quoted context omitted.

JavaScript has plenty of libraries covering the basics. Here a few: https://github.com/nicolaspanel/numjs https://www.npmjs.com/package/fast-math https://smartbear.com/de/blog/2013/four-serious-math-librari... That's not the problem. The problem is mindshare and network effects. When analyzing why Python is used one way and JS another we're tempted to retroactively rationalize this with something fundamental about th…

The first repo has one core contribitor who hasn't been active since June 2018. https://github.com/nicolaspanel/numjs/graphs/contributors I sincerely believe it is possible for JavaScript to be a viable language ecosystem, but there is dire need for cohesion, collaboration, and longevity. As it stands, there are so many potentially viable projects strewn across the NPM landscape like old, discarded toys. I'm not awar…

It is worth mentioning the Danfo project from a sibling comment: https://danfo.jsdata.org/

Re: JavaScript for Data Science

#23

Post by HWR_14 »

bryanrasmussen wrote: post #17
beforeolives wrote: post #2

I know that data science is a broad and somewhat vague term but this - We will cover: Core features of modern JavaScript Programming with callbacks and promises Creating objects and classes Writing HTML and CSS Creating interactive pages with React Building data services Testing Data visualization Combining everything to create a three-tier web application - this isn't data science.

nobody ever writes books assuming you know how to use the language, I suppose it decreases customer base.

It decreases the amount of boilerplate "how to program in X" text you have to write. Producing text, especially novel text, is expensive in a non-fiction book.

Re: JavaScript for Data Science

#24

Post by uryga »

11235813213455 wrote: post #7
danpalmer wrote: post #3

I don’t want to repeat the old and tired JavaScript hate, but this just isn’t a great idea. I’d suggest that there are 3 important primitives for data science: flexible numeric types, fast math/algorithm libraries, and data manipulation being easy. JavaScript doesn’t really have any of these. Numbers are 64bit floats only - no integers, no big numbers. There aren’t equivalents to Numpy/Pandas/Scikit Learn, and the la…

I don't see JS as less powerful than Python for data science, it's faster than Python, or can use bindings just like Python. JS is maybe less commonly used than Python in data science nowadays, but I wouldn't be surprised if this changes in next years. There are equivalent libs like tensorflow-core, there are native features like BigInt, and there are libs for 64bits floats (decimal.js, big.js). I'd be glad to spend…

> libs for 64bits floats (decimal.js, big.js)

both of those libraries are for arbitrary precision decimals, not floats.

Re: JavaScript for Data Science

#25

Post by Rainymood »

Really cool but no one needs this... as a data scientist learning javascript, teach me how to run data science models using javascript! That's where the real gold is... I'm even thinking of writing articles about this myself... JS is great for making things more tangible and interactive

Re: JavaScript for Data Science

#27

Post by bambam24 »

We run an experiment. We hired 4 Java developers all senior. And 1 Fullstack Javascript developer. Gave them the same tasks without telling them. The result: We got a Userinterfacd, aws serverless, and scalable infra within a week the task is comoleted by Single Javascript developer. And when we ask whats the status to 4 senior Java developer, they say they are still designing “thinking how to do it” At the end if second week, they were still sturggling with Gradle and supporting authenticafion.

And what they designed was to run k8s with EKS etc. Luckily they are no working in our company anymore.

Re: JavaScript for Data Science

#29

Post by danpalmer »

11235813213455 wrote: post #7
danpalmer wrote: post #3

I don’t want to repeat the old and tired JavaScript hate, but this just isn’t a great idea. I’d suggest that there are 3 important primitives for data science: flexible numeric types, fast math/algorithm libraries, and data manipulation being easy. JavaScript doesn’t really have any of these. Numbers are 64bit floats only - no integers, no big numbers. There aren’t equivalents to Numpy/Pandas/Scikit Learn, and the la…

I don't see JS as less powerful than Python for data science, it's faster than Python, or can use bindings just like Python. JS is maybe less commonly used than Python in data science nowadays, but I wouldn't be surprised if this changes in next years. There are equivalent libs like tensorflow-core, there are native features like BigInt, and there are libs for 64bits floats (decimal.js, big.js). I'd be glad to spend…

The fact that the number support isn’t part of the language is Linda the problem though.

When you’re writing data science code, the value is in the answer more than the process of getting to that answer. Anything that complicates that gets in the way. This is why things like Pandas are so popular despite having some questionable engineering. Using a library for big number support, having to get that to play nicely with other libraries, it all goes against the aims.

Now for data engineering it’s very different. I wouldn’t choose JS myself, but it’s a much more reasonable choice. For engineering the process by which you get the answer matters far more - is it scalable, testable, repeatable, etc. Having to use a library for big number support is fine.

It’s two very different ways of working and I’m still fairly convinced that JS is not conducive to the former.

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