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While I appreciate the hard work Hadley has put into this ecosystem, and I detest the language wars, I can't help but feel that the world would be a better plac

While I appreciate the hard work Hadley has put into this ecosystem, and I detest the language wars, I can't help but feel that the world would be a better place if Hadley had put his effort into python DS modules instead. Hadley's work puts R almost at parity with python (at best!) for munging, and for academics, this long-term trend of domain languages like R or SAS becomes counterproductive. It's as if he's leading us to a local optimum.

eanzenberg 10y ago
Hadley's packages seem geared more towards data munging and transformations (I regularly use plyr and ggplot from the 'verse) and not machine learning. In my experience R has better implementations of machine learning algorithms than sklearn and rstudio is a better ide than any I found in python.
- projectramo 10y ago
  Not arguing that your statement is right or wrong, but I suggest checking out Spyder for python. I go back and forth between the two, and though I hate the syntactic gear shift, they are quite similar.
  - eanzenberg 10y ago
    I have tried Spyder before. It was too buggy and crashed a few times on some light scripts. This was around June 2015.
RA_Fisher 10y ago
S (R's ancestor) was developed in the mid-70s and 80s, at least a decade before Python was written. Then couldn't your argument be applied to those working on Python data science tools? Variety is the spice of life. :)
- jhbadger 10y ago
  No, because the issue isn't that new programming languages and their libraries shouldn't be developed (and I'm a big fan of new languages with new paradigms) but whether the new languages should be general purpose or not. I'd argue that the development of S was misstep, and one which would have been completely forgotten by now if not for R and the libraries written for it.
  - hadley 10y ago
    No, one language (Python) isn't the right tool for every job.
  - RA_Fisher 10y ago
    Before S there were onerous Fortran routines. Rich Becker, one of the authors of S gave a really interesting talk about this at the useR conference this year, you should check it out if you haven't already: http://blog.revolutionanalytics.com/2016/07/rick-becker-s-talk.html http://blog.revolutionanalytics.com/2016/07/rick-becker-s-ta... You say that developing S was a misstep, what decision would you have made instead? Build on Fortran?
    - jhbadger 10y ago
      option 1) S was created at AT&T, the home of UNIX and C. Imagine if statistical functionality had been made a standard part of C rather than developing a new language. While C is maybe not that popular anymore, current languages like Java and C# inherit from it, and we would have a world in which statistical functions were taken as given as part of the default libraries of any language. option 2) Use another standard language like LISP. This actually was done in the excellent LISP-STAT system. Unfortunately it came out at kind of the wrong time for LISP. These days LISP is kind of undergoing a renaissance with Clojure, Racket, LFE, etc., but in the 1990s it was more associated with the failed AI efforts of the symbolic school and LISP was just seen as this weird thing with lots of parentheses by many people. The thing is I use R every day. But like everybody else, I bury it under lots of add ons like Hadley's and others to make it palatable by hiding as much of the absurd R syntax as possible. That's like dumping ketchup on foul tasting food. Is this really what we want to do?
blahi 10y ago
And I wish exactly the opposite - not to have every thread deailed with someone claiming "Python is better". No, it's not. (see what I did there?) But no, seriously, it's not.
projectramo 10y ago
It is interesting that Wes McKinney said that he had started Pandas so that R wouldn't dominate data science. (I am paraphrasing, but I think it was at the beginning of his pandas book). Now I happen to be a pandas person myself, and I am glad he did it. If someone had advised Wes not to spend his time on python and just focused on making R better, I would hope he would not have listened to that person.

eanzenberg 10y ago

Hadley's packages seem geared more towards data munging and transformations (I regularly use plyr and ggplot from the 'verse) and not machine learning. In my experience R has better implementations of machine learning algorithms than sklearn and rstudio is a better ide than any I found in python.

projectramo 10y ago
Not arguing that your statement is right or wrong, but I suggest checking out Spyder for python. I go back and forth between the two, and though I hate the syntactic gear shift, they are quite similar.
- eanzenberg 10y ago
  I have tried Spyder before. It was too buggy and crashed a few times on some light scripts. This was around June 2015.

RA_Fisher 10y ago

S (R's ancestor) was developed in the mid-70s and 80s, at least a decade before Python was written. Then couldn't your argument be applied to those working on Python data science tools? Variety is the spice of life. :)

jhbadger 10y ago
No, because the issue isn't that new programming languages and their libraries shouldn't be developed (and I'm a big fan of new languages with new paradigms) but whether the new languages should be general purpose or not. I'd argue that the development of S was misstep, and one which would have been completely forgotten by now if not for R and the libraries written for it.
- hadley 10y ago
  No, one language (Python) isn't the right tool for every job.
- RA_Fisher 10y ago
  Before S there were onerous Fortran routines. Rich Becker, one of the authors of S gave a really interesting talk about this at the useR conference this year, you should check it out if you haven't already: http://blog.revolutionanalytics.com/2016/07/rick-becker-s-talk.html http://blog.revolutionanalytics.com/2016/07/rick-becker-s-ta... You say that developing S was a misstep, what decision would you have made instead? Build on Fortran?
  - jhbadger 10y ago
    option 1) S was created at AT&T, the home of UNIX and C. Imagine if statistical functionality had been made a standard part of C rather than developing a new language. While C is maybe not that popular anymore, current languages like Java and C# inherit from it, and we would have a world in which statistical functions were taken as given as part of the default libraries of any language. option 2) Use another standard language like LISP. This actually was done in the excellent LISP-STAT system. Unfortunately it came out at kind of the wrong time for LISP. These days LISP is kind of undergoing a renaissance with Clojure, Racket, LFE, etc., but in the 1990s it was more associated with the failed AI efforts of the symbolic school and LISP was just seen as this weird thing with lots of parentheses by many people. The thing is I use R every day. But like everybody else, I bury it under lots of add ons like Hadley's and others to make it palatable by hiding as much of the absurd R syntax as possible. That's like dumping ketchup on foul tasting food. Is this really what we want to do?

blahi 10y ago

And I wish exactly the opposite - not to have every thread deailed with someone claiming "Python is better". No, it's not. (see what I did there?) But no, seriously, it's not.

projectramo 10y ago

It is interesting that Wes McKinney said that he had started Pandas so that R wouldn't dominate data science. (I am paraphrasing, but I think it was at the beginning of his pandas book). Now I happen to be a pandas person myself, and I am glad he did it. If someone had advised Wes not to spend his time on python and just focused on making R better, I would hope he would not have listened to that person.