R generation

https://rss.onlinelibrary.wiley.com/doi/10.1111/j.1740-9713.2018.01169.x

by kgwgk • 8 years ago

74 62 8 years ago

rss.onlinelibrary.wiley.com

clircle2• 8 years ago

I'm a statistician that knows just enough about computer programming to be dangerous. It's hard to overstate how incredibly important R is to my discipline. No other language allows me to express my thoughts and prototype statistical ideas quickly and effortlessly.

If statistical programming was still stuck in the SAS era, I think there is a non-zero probability I would have lost interest in the profession years ago.

et2o2• 8 years ago

Glad you're still interested! I agree–R is light-years ahead of the competition (Python, essentially) in most statistical domains. It seems to fit the workflow better.

skydaddy• 8 years ago

Light years ahead? It doesn't even support 64-bit integers. The R language cannot count past 2.1 billion. In 2018. Don't get me started on the package system.

gaius• 8 years ago

My heuristic is: if my program is going to be 80% NumPy and friends anyway then R is probably better but if it’s going to be only 20% (e.g lots of user interface code or whatever) then Python is better. I probably wouldn’t use R for anything end-user-facing unless it was via Shiny, whereas I might use WxPython for a desktop app.

For interactive, exploratory/research use R in RStudio beats Python in Jupyter hands down.

zaarn6• 8 years ago

Had to learn R for a statistics course. It was honestly the worst programming language I've ever used and I've once wrote something in Malbolge.

The package system is absolutely horrid, a barely working mess if I ask it anymore complicated than "install package, any version is fine". Installing older packages because my distro lacked a compatible library for the newest was met with rather bizarre error messages. I think Latex has solved this much better. Even NPM solved this better. If NPM has solved package managing better than your solution it's time to rethink your life choices because that is a very low bar.

The object and type system seems to be made of wet tissue paper, I always feared that staring at the code too long might break it. It also doesn't help that every package has invented a completely new way to pass parameters, how to name parameters and functions and how it all sticks together. Also nevermind trying to read numbers larger than a signed 32bit number, R can't handle anything beyond 32bits for reasons that aren't entirely clear to me. Though last I tried it was very happy to just dynamically convert to a float32 instead which immediately makes it worse than Javascript because atleast Javascript's Number type is consistently a float and doesn't magically turn into the burnt remains of my hopes and dreams.

On top of all that horrid stuff sits R Studio. When first installed on my computer, R Studio was of the opinion that the best option was to install itself as default program for EVERY SINGLE FILETYPE completely ignorant on if it understands it. I'm still trying to cleanup my laptop from the mess it made. The IDE has varying opinions on how to write programs, usually none of the good ones. It also likes to sprinkle it's caches and configs and other files into every corner of my filesystem. Every folder is Free-For-All for this IDE. My home directory should not be used to re-enact scenes from Battle-Royal shooters, especially not by tools meant for developing software.

It's not light years ahead of the competition, it's not even competing. It's sitting on the sidelines trying not to fall over from the stress of being outside and exposed to the elements.

I'm happy I passed my statistics course because I will never ever touch this language again. Ever. I'm still cleaning up the pieces from using it for only half a year and I would rather port the Linux kernel to Brainfuck before using this language.

Sorry to unload all of that on you but I'm very frustrated with R.

bigger_cheese• 8 years ago

That's really interesting to hear. I am an engineer rather than a statistician so my usage is probably different (Mostly analyzing and modeling process data).

SAS is so entrenched in my organisation and there is such a long history of legacy SAS code that I feel like at this point it is probably impossible to migrate out of it.

How did you end up adopting it was it an organisation wide thing? I was able to get my work to send me on R course last year (Based around Microsoft R-open product).

I've found it pretty difficult to get other people here to switch the barrier is just a bit higher (functional language which people aren't all that comfortable writing etc) and lacks all the legacy code.

safgasCVS2• 8 years ago

At our company adoption of open source tools happened bottom-up despite us having licenses for SAS, SPSS, Emblem etc etc. you name it we have it. But even having easy access to these tools people here still found downloading R/Python was easier still than logging a call with IT and having to manager approval to install software.

Oh and on the legacy code - no it never goes away. The handful of SAS programmers around 20 years from now will be able to charge fortunes to maintain those legacy systems.

Cieplak• 8 years ago

If you want to sprinkle some type safety onto your R, check out this lovely piece of kit:

https://tweag.github.io/HaskellR/

amrrs• 8 years ago

R and Rstudio have been my primary bread and butter maker. You might argue that Rstudio has financial interest in growing R community but it's fair and it has helped overall R as a language entirely (not just as statistical one). Hadley Wickham's tidyverse is an amazing example of how one can simply get stuff done. Along with %>% pipe it is almost like idiomatic python. The ecosystem is amazing, I can write a web scraper in a couple of lines of code as simple as beautifulsoup. I think that's the strength of R. The intuitive UI and easy setup of RStudio just help someone get started with no hassle. That's a key I believe. I have also trained non-programmers and they managed to do data analysis in R using tidyverse in a matter of a month or two max.

remarkEon• 8 years ago

R was the first language I learned (I ... do not recommend this) and while I don’t use it Day to Day at work, I’m always using it for fun side projects about everything from baseball statistics to urban planning. I’m not a professional statistician, by any means, but fully appreciate the work the community does with this toolset.

sampo• 8 years ago

Thinking about the long run: Is there any version of the future where the best and largest library of statistical procedures could be somewhat language independent, and not organically part of a small language that itself is an unholy alliance of a matlab-like quick-and-dirty syntax and a hobbyist-level scheme interpreter runtime?

disgruntledphd23• 8 years ago

If you really want this to happen, you should probably start contributing to Julia.

msaharia2• 8 years ago

There is an xkcd comic for this one on JavaScript Frameworks.

_Wintermute• 8 years ago

R was the first programming language I learned and I still use it a couple a times a week for work, but it wasn't until about 2 years into using R when I started learning python that I realised programming isn't difficult and frustrating, R is just badly designed.

j7ake2• 8 years ago

In my opinion, R is the best language for quickly exploring, iterating models, validating the models, and repeating the cycle. I would be curious to hear whether Python, which I use for preprocessing the data into flat tables, is as good as R in this domain.

Also ggplot2 and tidyverse packages are powerful for accelerating your iterative cycles.

curiousgal• 8 years ago

Absolutely not! If you're given a dataset and you're trying to fit a model or even run exploratory analysis, Python doesn't even come close to R. Even with Jupyter, the experience is not as smooth as R+Rstudio.

kgwgk2• 8 years ago

Or R+ESS :-)

laichzeit02• 8 years ago

Except if you like Vim keystrokes. The R Studio implementation (as I understand it's just the ACE library) is really crap.

I find even the Juptyer-notebook Vim plugin is better than the R Studio implementation :(

FranzFerdiNaN2• 8 years ago

I've tried both R and Python for data analysis and data wrangling and the experience with R was a whole lot better for me (I work as a business intelligence consultant). Python is really steeped in programmer culture, which you notice in everything from its user base to its manuals. Which is great for people who want to learn programming or study CS or so.

But I'm not a programmer and I don't want to be. My biggest program ever written is maybe 150 lines to covert a mess of excel files to something usable. Programming is a necessary means to an end for me to do my job, but every time I tried to learn actual programming it bored me to tears. R, while I fully admit has a syntax which is clunky at best (although the tidyverse really helps here), does exactly what I need. Its users are all active in roughly the same space (data analysis in all its forms) so finding help is easy. The community is incredibly friendly, easily found on Twitter with the #rstats tag. It has packages for everything I would ever need. Basically, R helps me get things done, which is all it needs to do for me.

fritkot• 8 years ago

I think your post illustrates well why both languages are important to have. I also work in the Business Intelligence - space, but my job is usually more focussed on setting up data pipelines and developing a small specialized web app here and there. So if I'm already doing that, and I do analysis on top of that, of course I'm going to pick Python, because I can stay in the same ecosystem and I already have a better feeling for how things are going to work. But this wouldn't make sense at all for someone who generally works more on strategy and decision making and wants to dig a little deeper from time to time.

Although when people ask me for a recommendation on what to learn, and they're actually interested in programming and building things themselves, I always recommend them to at least give Python a shot and see if they like it, as it then also gives them the possibility to do a lot of other things with the language.

zestyping• 8 years ago

It's really interesting that there are such divergent opinions on R and Python. I'm curious why some people seem to find R incredibly frustrating and Python entirely sensible, and others find R miraculous and smooth and Python inaccessible.

Is there some set of improvements to Python that would make it popular with R users, or vice versa? Or is it a fundamental difference in taste that will never be bridged?

SJetKaran• 8 years ago

I think one reason people may not readily like R, is because it is a functional language. Most programmers are comfortable with object oriented programming rather than the functional style. It takes a while to get used to it.

I have seen people who started programming with R, and they get fluent in it pretty fast.

krutulis• 8 years ago

I've been programming for a long time and had to learn R a few years back for a series of projects. The documentation and community seemed to me, as a newcomer, to be very focused on how to solve particular statistical and modeling problems, and I was almost always able to do what needed to be done relatively quickly. (Python documentation and communities, in contrast, span all kinds of applications that can be difficult even for an experienced programmer learning Python to sort through and evaluate. I can also imagine the migration to 3.x has been a challenge for newcomers.)

Although I enjoyed learning and using R, as a CS person I was bothered that I understood how to do X in R, but I had no clue about what was happening when I did X. I found this paper to be particularly useful in describing R from a CS perspective: http://www.lirmm.fr/~ducour/Doc-objets/ECOOP2012/ECOOP/ecoop...

R generation

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