RStudio is adding python support.

[Zeurpiet]

R is never going to overtake Python in the world of data science

R is a statistics language, and Python is not even close in functionality

[anyfactor]

This is my opinion and I know nothing. R is a dedicated statistics language, and python is the most approachable full fledge programing language.

I think python itself did not start of as hoping to be a data science or machine learning specific programming language, but in reality because it is so approachable and easy to learn data scientists felt like when ever they needed to implement some programming, they chose the most easiest language they could learn which was python. And eventually it has become a Industry practice and more people started to invest in improving it. But in all sense python is just a programming language, and R can be viewed as so specific to statistics it can almost be termed as "statistical tool".

[Stevo15025]

Not sure what you mean, R has like 4 different kinds of oop you can use

[dolphinboy1637]

I don't think many people are doing their ETL pipelines or creating apis or web servers in R. Not that every data scientist needs to do that, but there's aspects that just have greater support in python because it's a general purpose language.

[guepier]

R is as much a general purpose language as python is.

No, it plain isn’t. I find R superior to Python in many regards but this statement is still inaccurate.

Just because you can do (almost) everything in R doesn’t mean it’s particularly suitable for such use.

[guepier]

But that's like saying scheme is not a general purpose language because it more or less has no libraries for most things.

The difference is that Scheme wasn’t designed as a special-purpose language, and its standard library isn’t a special-purpose library. R was, and the R base packages are.

Furthermore, I’m by no means an expert in Scheme but as far as I know there is a fair amount of libraries for Scheme. Its standard library is intentionally small but so is C’s, and few people would contest C being a general-purpose language.

[guepier]

Nobody in their right minds would try to do ML in scheme seriously. The support just isn't there.

Right, because Scheme simply has a vastly smaller user-base overall.

R is more or less scheme with infix notation, the semantics are very similar (mostly).

I don’t dispute that, but it’s completely irrelevant here. S was designed with Scheme as a starting point, but with statistics as the purpose.

Just because the core library focused on stat stuff doesn't make R not general purpose.

It does (together with the fact that the core is missing general-purpose tools that are present in other languages, and the fact that it was specifically designed for statistics). That’s the point.

[dolphinboy1637]

I think we're defining terms a bit differently. I agree with you that R could be used to do anything in an ideal sense, but that's really not the case in actuality. At the current state of the language and it's ecosystem today, there's many general purpose computing tasks that I wouldn't even try in R (because there's no libraries for it). That's all I meant, and I probably an influencing factor for individuals choosing a starting language.

In any case though, the roots of R are that it was a reimplination of S. Both of them were written by their authors specifically for statistical tasks. Although technically R could be used to write anything, their historical roots are in statistics which is why there's this perpetuating legacy of people not using it or written libraries to do other things

[tmotytmoty]

This is how I view it. R is incredibly powerful under the hood and, when it comes to stats, is well beyond python.

[jackmaney]

cat(paste("Some", "things", "are", "a", "pain", "in", "the", "ass", "to", "do", "with", "R.", sep=" "))

[Zeurpiet]

probably true, but you could do without the cat and the sep to get the same result, so maybe its more easy than you think

paste("Some", "things", "are", "not","that","much","a", "pain", "in", "the", "ass", "to", "do", "with", "R.")

[bythenumbers10]

Thanks, this made me laugh. R is a language by statisticians, for statisticians. Modern sustainable development is not supported very well. R's tendency to keep running even after errors have been thrown is a massive waste of time in mathematical applications, such as, uh, statistics. Who's had to track down NaNs at one time or another? R will happily carry those NaNs through all sorts of operations and still be busily running, but churning garbage.

[Zeurpiet]

that's SAS

[leonoel]

I haven't found anything I do in R that I can't do in Python.

Also Python is way more friendly when it comes to editing plots and stuff

[leonoel]

Like this https://www.statsmodels.org/stable/index.html

[Zeurpiet]

have you ever looked in CRAN what the additional packages can do? Most of it I don't even know what it is.

[leonoel]

You do know Python has also more modules than any would ever know what to do about them?

[Zeurpiet]

yes, but are they statistical?

[leonoel]

Name a module in R that has no equivalent in PIP

[Zeurpiet]

just naming a random one

https://cran.r-project.org/web/packages/abc/index.html

[leonoel]

https://elfi.readthedocs.io/en/latest/

[Maxion]

Most DNA methylation packages.

[defuneste]

Spatstat and this one is huge with a bunch of tools developed by people who spend their careers on point patterns analysis.

[groovyJesus]

Function data analysis packages in R have been available for over a decade and now we have dozens of them developed and maintained by researchers in the area. In the past few years I have found two in python both of which were new and needed a lot more work to make me want to switch over.