Comments on: Is R Required for Data Science? (my opinion) https://data36.com/is-r-required-for-data-science/ Learn Data Science the Hard Way! Sun, 25 Oct 2020 13:56:20 +0000 hourly 1 https://wordpress.org/?v=6.7.4 By: Tomi Mester https://data36.com/is-r-required-for-data-science/#comment-190989 Fri, 23 Oct 2020 20:24:44 +0000 https://data36.com/?p=5484#comment-190989 In reply to Alessandro.

hey Alessandro,

Thanks a lot for the comment!
I’d not go that far that “R is not created by programmers” — it certainly is.
But you are spot-on that Python is just more polished from that consistency perspective. (It’s not an accident that currently we have Python3 and not 2 or 1.) It’s used by a lot of people in production, so as you said, they had to solve that it won’t break because of inconsistency or compatibility issues. We that being said, there are some of these in Python’s data science packages. But there are great solutions for these (e.g. Conda/Anaconda).

So that’s actually one more reason next to Python!
Tomi

]]> By: Alessandro https://data36.com/is-r-required-for-data-science/#comment-190988 Fri, 23 Oct 2020 10:13:55 +0000 https://data36.com/?p=5484#comment-190988 Hey Tomi!
Nice post as usual. I had been using R for years for social statistics and it’s just during the pandemic that I gave Python a try. I love it some much that now I’m considering not coming back to R, except when needing that one very specific statistical library.

The reasons are many and similar to what you say regarding the syntax and the fact that Python is a general language. I also have the following impression, it would be interesting to know what you think about it:

Since R is mainly developed for and by statisticians, instead of programmers, a lot of how it is used just feel less polished and professional. For example, in my experience with R, everything seems less careful when managing requirements. I’m not sure if this is due to the language itself or due to the culture of the people that use R (as I said, most are not programmers but statisticians), but I’ve had many headaches with scripts (from online courses, colleagues, etc) that don’t run because one of the packages used changed its syntax 3 days ago.

In the Python world everyone seems to take more care by providing you with requirements files or simply telling you which versions to use, and setting up virtual environments to manage this is very easy.

Another example: the R package for Ubuntu had an issue some years ago (and I was affected by it) because the maintainer used a short apt-secure key ( http://rubuntu.netlify.com/post/changes-to-cran-ubuntu-webpage-regarding-apt-secure-key/ ). Some computer science friends of mine laughed telling me this happened was because R is not really developed by programmers. I didn’t really understand what they meant at the time, but after learning Python and seeing how unpolished R feels sometimes it is clearer what they were pointing to.

That’s my grain of salt, keep up the good work! 😉

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