Hi all, Some additional observations from the R vs. Python world in my current context:
I'm finding that there is another natural divide between primary users of each language, which deals with how they actually *use* the tools. From my experience, R users expect to be working in R studio (or a similar IDE), and while there are Python IDEs, etc., I find most Python users to be *in general* more familiar with the command line. I think this has a direct impact on how users perceive of the usefulness of each tool. I have two anecdotal examples. I recently made an R CLI to do a simple analysis; however, I found that when I went to shop it around my research group, no one wanted to use it -- they'd rather a script or module that they could run directly in their IDE (that is, their workflow is: open IDE, open file, click run). Further, I learned recently that the dplyr package (very popular in the R ecosystem) has specific functions for "programmatic" use, e.g., summarize_each() vs. summarize_each_(), again speaking to the use of the tools in a "hands-on" mode, rather than a "headless" mode. With the use if IPython, we teach lessons for both languages in a very IDE-friendly envrionment, but I have always provided at least one example of running files from the command line when I teach the SWC stack using Python. Do teachers of the R stack also do this? Is it important to make such a distinction? Cheers, Matt On Fri, Apr 1, 2016 at 3:01 AM, Vilbig, Kevin P <[email protected]> wrote: > Most of the really rad tools out there use polyglot stacks, anyway. > > > There is no reason why you can't run a bash script that runs a python > script (or some weird ancient legacy tool) to run some analysis that pipes > a final CSV into an R script's dataframe for plotting using the prettyness > of ggplot. > > > Programming Languages are for people. > > > ------------------------------ > *From:* Discuss <[email protected]> on behalf > of E.W. <[email protected]> > *Sent:* Thursday, March 31, 2016 2:51 PM > *To:* Matthew Gidden > *Cc:* [email protected] > *Subject:* Re: [Discuss] Any tips for learning R and Python? > > If I am recalling things correctly, and this will certainly be contentious > for some folk, but Python is a general purpose programming language while R > is a statistical programming language. > > I think it is generally the case that with enough hacking you can > accomplish nearly any task with any tool, but some tools are more geared > towards performing certain tasks. I like to stress to brand new students > that the question is never "can" but "should" or "which is easier?" when it > comes to this kind of thing. Sometimes even a brutal hack is more efficient > or mentally easier to accomplish than fighting to learn something in a new > language that you aren't comfortable with. "I know this could be better R, > but I need to get the job done. [translation: please don't judge my for > loops]" is a completely sane and normal reaction. Programming communities > or those offering consultations shouldn't turn into handwriting judges. > > This doesn't mean we should reject or toss away the importance of language > idioms, but turn our attention to respecting that it's the research content > that matters and not which plotting library or whatever else they used. I > think that SWC does a great job of this balance and showing it in action. > > I don't believe there is a clear line to be drawn between Python and R, > except in the cases when a specific package is needed and does not exist > for that other language. The choice between Python or R is never *just* > about the task, but also about the skills, experiences, and support > networks of the person who will be writing the code for that task. > > Elizabeth > > _______________________________________________ > Discuss mailing list > [email protected] > > http://lists.software-carpentry.org/mailman/listinfo/discuss_lists.software-carpentry.org > >
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