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Big Book of R

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288 points sebg | 2 comments | 10 Apr 25 17:34 UTC | HN request time: 0s | source
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cye131 ◴[10 Apr 25 23:51 UTC] No.43649039[source]▶
R especially dplyr/tidyverse is so underrated. Working in ML engineering, I see a lot of my coworkers suffering through pandas (or occasionally polars or even base Python without dataframes) to do basic analytics or debugging, it takes eons and gets complex so quickly that only the most rudimentary checks get done. Anyone working in data-adjacent engineering work would benefit from R/dplyr in their toolkit.
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wwweston ◴[11 Apr 25 00:20 UTC] No.43649208[source]▶
what’s the story integrating R code into larger software systems (say, a saas product)?

I’m sure part of Python’s success is sheer mindshare momentum from being a common computing denominator, but I’d guess the integration story is part of the margins. Your back end may well already be in python or have interop, reducing stack investment and systems tax.

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kerkeslager ◴[11 Apr 25 03:41 UTC] No.43650307[source]▶
This is, I think, the main reason R has lost a lot of market share to Pandas. As far as I know, there's no way to write even a rudimentary web interface (for example) in R, and if there is, I think the language doesn't suit the task very well. Pandas might be less ergonomic for statistical tasks, but when you want to do anything with the statistical results, you've got the entire Python ecosystem at your fingertips. I'd love to see some way of embedding R in Python (or some other language).
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1. notagoodidea ◴[11 Apr 25 04:01 UTC] No.43650403[source]▶
There is a lot of way and the most common is shiny (https://shiny.posit.co/) but with a biais towards data app. Not having a Django-like or others web stack python may have talks more about the users of R than the language per se. Its background was to replace S which was a proprietary statistics language not to enter competition with Perl used in CGI and early web. R is very powerful and is Lisp in disguise coupled with the same infrastructure that let you use C under the hood like python for most libraries/packages.
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2. kerkeslager ◴[11 Apr 25 05:07 UTC] No.43650669[source]▶
> There is a lot of way and the most common is shiny (https://shiny.posit.co/) but with a biais towards data app.

I tried Shiny a few years back and frankly it was not good enough to be considered. Maybe it's matured since then--I'll give it another look.

> Not having a Django-like or others web stack python may have talks more about the users of R than the language per se. Its background was to replace S which was a proprietary statistics language not to enter competition with Perl used in CGI and early web.

I'm aware, but that doesn't address the problem I pointed out in any way.

> R is very powerful and is Lisp in disguise coupled with the same infrastructure that let you use C under the hood like python for most libraries/packages.

Things I don't want to ever do: use C to write a program that displays my R data to the web.