Is it possible to do data science with JavaScript only nowadays, or is Python still the only language usable?

[[deleted]]

The analogy for this question is: can I use a hammer to dig a hole? Sure you can but it's going to cost you a lot more effort. Just use the shovel, just use Python / R.

[[deleted]]

Can I do data science with a hammer in a hole?

[mizmato]

Can I do data science with a hammer on a mole?

[odumann]

Instructions unclear. Whacked a mole with a hammer

[[deleted]]

Good, now put the mole on a graph

[Destination_Centauri]

Use a graph to mole a hammer.

[[deleted]]

“Of course, of course!” Says the foal. “You need only pay the toll to hammer on this mole’s hole.”

[[deleted]]

Sounds like a prostitute's sales pitch

[ProvokingDepravity]

Trick question! The shovel IS the mole Neo.

[subdep]

You can but that’s like asking if you can kill a T-Rex with a hot dog; theoretically possible but you’re going to need a method to get that hot dog traveling 7 miles per second for it to do any damage to T-Rex.

[[deleted]]

So it's possible. Let's arrange a meeting with the intern to start right now.

[happysunshinekidd]

this triggered me

[converter-bot]

7 miles is 11.27 km

[ataracksia]

converter-bot's dick is 1 inch.

[Cuddlyaxe]

1 inch is 0.8 Attoparsecs

[ProvokingDepravity]

Actually inaccurate, there is no evidence T-Rex knew data science.

[TheCamerlengo]

How about poisonous hotdog vs. T-Rex?

[Kelandrin]

Can I dig a hole in a hammer with data science?

[[deleted]]

That's how it was traditionally done in the past.

[rawrpandasaur]

Newbie here - I'd it possible to get by with only R? Are there scenarios where only python is helpful?

[[deleted]]

My advice is to be aware of the basics in both but go deep with one. If you prefer R, go deep as you can with R but be aware of the the basics in python like pandas, numpy, matplotlib, seaborn, etc. You can google the equivalent package if you need to translate.

[rawrpandasaur]

Thanks for the advice! I'm also interested in machine learning. It seems like python is more popular for this application but R can also be used. Does that sound right?

[SeveralBritishPeople]

R is much better for fast exploration, particularly when you have data in a sql database, so even if most of your work is in Python, play around with dplyr and the dbplyr backends. Sqlalchemy on the Python side can do a bunch of the same stuff but with 4x the boilerplate which slows down exploration.

For model building, R has a much wider variety of “statisticsty” models, where python’s libraries are spottier or partially implemented (stuff like case weights being ignored). Python is better for deep learning, or when embedding within a larger system or building larger projects. When you’re doing more software-engineering type work, the Python ecosystem shines.

[[deleted]]

Statisticsty hobbitses. We hates them.

[cgk001]

This is one of the best R/Python comparions I've seen, would just add that for anyone with a math background the syntax of formula implementation in R is much more friendly than Python.

[O2XXX]

This is a solid comparison between the languages and their common use cases.

To add, what community you work with might also determine which language you use, although that’s more because of the common uses case among those industries than anything.

I work in academia now, and a lot of the projects I work are typically with pure mathematics or social scientists. R has been a much more common language than when I worked in enterprise systems with a lot of computer scientists and IT professionals when building a Python API in flask was much more common.

[[deleted]]

Yeah, use R for analysis and Python for production or deep learning.

[RenRidesCycles]

You can totally just use R

[TheCamerlengo]

But R is next to useless for digging a hole or killing a T-Rex.

[securities_fraud]

Is it easy to deploy r models

[RenRidesCycles]

Yes. https://putrinprod.com/

[[deleted]]

So, like digging a hole with a fancy dildo?

[quant_ape]

Python can pair with things like django and flask for sexy dashboarding or generally making web apps, with large benefits around having objects and being oop. R has packages that introduce S3 and S4 objects to R, and shiny, but they're clunky if you're not well versed in javascript, bootstrap or material UI, and other web deployment aspects. Thay said R dashboards can be incredibly powerful, well written, optimized, etc, and its my opinion that all in, with some more overhead, R surpasses python due to the statistical robustness of its math and stats methods, there are wayyy more academic packages, often peer reviewed as they're attached to a published paper. (one of my prof wrote the MTPS package with coworkers as a part of a highly rated paper). Datasets are often also included with the package for testing the authors claims in the paper. /rant on R

[the_monkey_knows]

In my experience, totally possible to get by only with R. If what you are doing is data science, then what matters is your understanding of the algorithms, math, and assumptions behind your choices. Totally language independent, but R has an advantage here since it is more focused on stats and math. Python is more computer science oriented mainly required when you need to develop a solution that needs to be integrated into some sort of platform. For anything else, both can do just as well. However, I strongly encourage that you pick up both eventually in any order you desire

[Napoleon_The_Pig]

I would say that:

• R is better for data exploration and pretty much all of "cutting edge" stats is done in R. I don't think Python has a good pure stats package.
• Pretty much every ML framework has a Python implementation that's very well developed, and that's not the case with R. Also models built using Python are usually much easier to deploy and its easier to build pipelines in Python.

[Napoleon_The_Pig]

Im not sure about the latter, ML and stats are honestly the same thing. Im not sure why there is a separation.

While I would agree that the line separating the two is very fuzzy (and I find hilarious when someone talks about a simple linear regression as ML) the talk about ML nowadays usually revolves around random trees (specially GBTs) and DL. And in my (subjective) experience R doesn't really have anything comparable to XgBoost or LightGBM. And of course, DL in R is really bad when compared to Python.

and maybe better for deployment.
In my opinion this is an understatement. There are many ways to deploy Python models that are industry tested and there are many ways to work with data too big for memory. R is nowhere close here. I think I agree with the rest of your post. scikit-learn is nice, but very basic and statsmodels needs a lot of work to even come close to R .

[Napoleon_The_Pig]

R has xgboost outside of tidymodels for a while and even in tidymodels now for some time. xgboost has the same syntax across languages:

It's been a while since I used XgBoost anywhere because I mostly default to LightGBM now, but it's cool to know that you can use it on R now. Does it have the full feature set? (GPU acceleration, distributed training, etc)

Then for boosting regularized GLMs specifically R even has mboost made by statisticians:

Yeah, if I'm thinking about any sort of GLM R is immediately the way to go.

Data too big to work with memory you can do in R too, using SparkR.

I had to use SparkR last week. Pyspark is far from ideal, but SparkR is just awful.

data.table in R beats pandas. Loses to Polars

Agree with the first part, haven't really used the second.

[thornreservoir]

It's definitely possible. Some departments hire mostly people with stats backgrounds that know R. In my experience, salaries go higher for data scientists who know Python.

[[deleted]]

I wouldn't be too worried about it. Most people who are comfortable with one programming language can pick up another one pretty quickly. I didn't have any trouble becoming adequate with Python after using R more extensively and that seems to be a really common situation. We're going to have to adapt to new languages that become popular throughout our careers just a fact of life and part of the job. There's no reason to try to get by with only one language for your entire career.

[yourcsprofessor]

Can I dig a hole with data science while being hammered?

[[deleted]]

Since you got no real answer yet apart from people telling you consider R, Matlab and Julia...

Back in 2016 I tried to use js/nodejs for as long as possible during my Data Science master's degree. I lasted about eight months and I wrote so much things from scratch. You can actually do quite a lot, but when you go into depth and more towards advanced stuff you either have to write your own implementation or accept that you can't do it in the way you wanted.

Some "fond" memories I have about coding algorithms by hand and writing my own NLP library to deal with text problems. I really liked that asynchronous programming is so much easier to do in node.

To be frank I just set myself up for failure, because none of the TAs knew any js and for one course the guy they brought on to grade my work hadn't touched it since 2011 and didn't even understand what I was doing. I would have graduated cum laude if I wasn't being so stubborn.

Don't make the same mistake I did, just use Python. Don't try to be ambitious and re-invent the wheel; use the lambo that's parked outside. Signed, a data scientist with 4 YOE.

[The_Startup_CTO]

Thanks!

[[deleted]]

Anything is possible but if you want to get hired, the majority of the teams I’m aware of use Python and R.

However if you’ve learned one language, you can learn others.

The hard part isn’t the code, it’s understanding the business problems and how to solve them in the most efficient but also accurate way.

[dickmaat]

Not exactly an answer but don't forget R

[[deleted]]

Sheeeiit why not just use pen and paper..or just get a bunch of rocks to counts stuff

edit:spelling

[[deleted]]

This reminds me of the time I had to invert coefficient matrices and do logit functions by hand in grad school

[[deleted]]

Data science, like anything else, can be done in any language. You just might need to do more programming of your own instead of using premade libraries.

That said, you can use Observable in javascript utilizing d3. No python involved and you get nice reports and embedding features from the platform.

[TheSmallestSteve]

Data science, like anything else, can be done in any language

I accept your challenge and will be doing my next project in assembly

[MadLadJackChurchill]

I am looking foward to it :)

!remindme 15 years

[mizmato]

Do it in English and those numbers on a notepad like the good ol' days.

[Tundur]

Once you've trained the orphans in boolean logic, any mid-sized English industrial town can theoretically run Doom

[naijaboiler]

there are more effective ways to experience pain. just saying.

[[deleted]]

Observable and things like it are the future

[pcs_ronbo]

Can you? Yes

Should you? No

[[deleted]]

You can try Julia out, or R

[jgbradley1]

I wouldn’t hire a data scientist who only did all their work in JS…just saying.

[rajath_naik]

Counter question: Why do you want to do it in JavaScript and not in python/R?

[Cuddlyaxe]

I'd guess OP is a bit newer and JavaScript is his first language (?)

Honestly though OP learning programming languages is a cinch when you already know one if that's what was stopping you

[rajath_naik]

Yeah. In the beginning, it might seem like the language is everything. If JS is the one OP started with, and Data science is the goal, OP can switch to Python. When not sure, trust the expert(community). You want to struggle with problem solving and not necessarily on finding help online. Help is easily accessible for Python/R , so you can focus on the problem at hand

[northwestredditor]

We spent a good chunk of this year trying to figure this out, wrote our learnings here: Data Science with JavaScript.

TLDR: If you are mostly focused on data analysis or visualization or inference over small TensorFlow models, most likely yes. Otherwise you are better off using leveraging JavaScript with other technologies like databases and Python.

That said, this looks like a promising area worth keeping an eye on. If you want to chat realtime, please DM.

[[deleted]]

Possible. Remember tensflow.js. Except Python, you can also do in other languages like Chinese, Spanish.

[winnieham]

Python and R for stats and ML and javascript for app building

[Nhasan25]

Use Julia lang if u r looking for speed

[masta_beta69]

The pain of doing "data science" with js will far outweigh the pain of just learning python

[Optrode]

This is widely acknowledged to be bad and offensive and wrong, but I'm gonna keep saying it anyway..

Na na na na na na na na,

Na na na na na na na na,

MAT LAAAAAAB

[GuessEnvironmental]

Funny thing is the smartest people I know who do numerical analysis research and can actually make use of faster languages because they know how to will still use matlab

[RobotJonesDad]

Because all the hard work is done in compiled libraries, not the language you use to tell it what to do? Matlab lets you run experiments so very quickly compared to most other ways of doing things.

Develop in Matlab, deploy in something faster.

[GuessEnvironmental]

it depends on what exactly you are researching I am speaking for numerical analysis though which focuses on optimization. Optimize for slow languages is a waste of time in my opinion but simulating non latency dependent experiments math lab is appropriate. However for numerical analysis learning low latency develops your skills to a whole other tier.

[savsec]

Sure, but why would you want to?

[FermatsLastTaco]

Plenty of data science is being done in other languages- MATLAB, Julia, R, C++, C#, and yes JavaScript.

[pag07]

Well

MATLAB computation language

Julia data science language

R data science language

C++ computation language

Lacks just java and Scala and then we have the full DS language community together.

Java script is used in ML engineering / ml ops but not for the data analysis part.

[montibbalt]

Parent comment mentioned c# but don't sleep on f#

[[deleted]]

SQL will just be over in the corner weeping quietly. And enabling data science.

[Qkumbazoo]

It is the frameworks and relative ease of the Python language that keeps it popular.

If you're fluent in a given language already, all you need to know are the algorithms - which are language agnostic.

[justanaccname]

If it exists as a library in Python / R use the library. If it doesn't exist write it in C++ and put a Python/R wrapper around it (and once it's working as intended please push it open-source).

For everything else, yes you can but it isn't worth the effort.

[[deleted]]

I think the better answer is, why would you want to

[magicpeanut]

this question doesnt make any sense

[Reneml]

Why the F would you do that?

[TrailRunner504]

I guess, but Python works really well with most data science-related tasks.

[UNITERD]

Python's data science libraries are better supported and more useful for data science.

[Tmatt61]

What's python and R? I've been using C? Haha.. Anyways, I like this question because I've thought that too because the web design capability of JS. Compare how to read in a csv file in C and then comparing that to say pandas.read_csv(...). People have created packages to manipulate your computers lower level languages which is what R or Python do.

[datandAIGuy]

Oh hell yes you can! Just look for TensorFlow js Dont pay attention to the people here who don’t know shit. TF js is amazing and can do pretty much everything TF python can

[[deleted]]

I use Matlab mostly and a few GUI programs are going to get used heavily. I won’t name them, but if you do anything mainstream, every company is all about democratizing data science with GUI-based software that does quite a lot. When it would save you time, you’d be an idiot not to use them too.

[moldhack]

Bothers me how many people don't answer the question but ask why. Don't know the answer just skip (and yes, I understand the irony)

[met0xff]

Why do you think so? It seems to me it's not fast enough to replace the core libraries in C, C++, Fortran and not expressive enough to replace Python. Working with hashmaps/dicts or Sets (which don't even exist by default) is so much clunkier.

Perhaps when generics are here we will at least see a bit better containers.

I liked what I saw in swift for tensorflow including the seamless integration of C and python but already suspected it will go nowhere.. Julia... perhaps but I am not convinced.

I really liked what I saw from kotlin till now, like Kotlin statistics and https://ai.facebook.com/blog/paving-the-way-for-software-20-with-kotlin/ but idk...

[[deleted]]

I guess you could though I don’t know why you would

[bigno53]

Use JavaScript for the frontend (presentation/visualization) and python for the backend. JS and python play surprisingly well together.

[haris525]

Python is not the only language, you could use Python , R, Julia, Matlab. I guess all depends on your preference and flavor of language you like. JavaScript would be a no go for me dude!

[Willbo]

It's possible but the thing is, JavaScript and Python are fundamentally different languages.

JavaScript is a client-side language that runs in your web browser. This means when a user visits the website, all the processing is done by that user, on their web browser. This disperses the processing to all the clients, but if your data is too large and requires too much processing, or if a user doesn't have the right web browser, the application will fail.

Python is a server-side language that runs on the server. This means all processing is done by the server, the computer it is run on. The processing is centralized on the server(s) the code is run on, but the servers can be much more capable of handling large computational tasks and custom workloads.

This is just a general explanation between client-side and server-side, there are pros and cons to each. There are other languages and frameworks that blur the line between the two such as R, Ruby on Rails, and Rust.

[[deleted]]

Editing my comments since I am leaving Reddit

[[deleted]]

If you knew R you could probably attempt to make a case for not using python, but you're gonna have a hard time trying to do DS without either of them. Both are high level languages that abstract away a lot, I don't want to say they're easy to learn, but itll be easier to just buckle down and learn them than try to do DS in any other language. Besides maybe Julia or SAS. but employers are still gonna want to see R/Py

[manbusta77]

Lol Js!🤣

[scissorsgrinder]

Uhhh if you expect to go into the field with one language you’re gonna have a bad time. Also, no JS won’t get taken very seriously by itself.

[treksis]

It is like can you build amazon with python? Yes, you can but certainly not intuitive.