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Big Book of R

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Re: Big Book of R

#31

Post by freehorse »

raffael_de wrote: post #27
kylebenzle wrote: post #23

Earlier quoted context omitted.

Yes but today I find little to no benefit over python

no plotting library available in python even comes close to ggplot2. just to give one major example. another would be the vast amount of statistics solutions. but ... python is good enough for everything and more - so, it doesn't really feel worth maintaining two separate code bases and R is lacking in too many areas for it to compete with python for most applications.

Until you need to plot anything more than a few hundred thousand data points, in which case ggplot is extremely slow, if it even manages.

Re: Big Book of R

#32

Post by shepherdjerred »

haberman wrote: post #14
thangalin wrote: post #7

Tangentially, R can help produce living Markdown documents (.Rmd files). A couple of ways include pandoc with knitr[0] or my FOSS text editor, KeenWrite[1]. I've kept the R syntax in KeenWrite compatible with knitr. Living documents as part of a build process can produce PDFs that are always up-to-date with respect to external data sources[2], which includes source code. [0]: https://yihui.org/knitr/ [1]: https://kee…

There is also Quarto, which I have had a good experience with: https://quarto.org/

I'm more excited about https://typst.app/

Re: Big Book of R

#33

Post by ekianjo »

kylebenzle wrote: post #23
MrLeap wrote: post #20

Earlier quoted context omitted.

If you started with SAS for statistics like I did, you'd see how absolutely civilized R is in comparison.

Yes but today I find little to no benefit over python

Tidy verse has a much nicer syntax than pandas and the like

Re: Big Book of R

#34

Post by Onawa »

shepherdjerred wrote: post #32
haberman wrote: post #14

Earlier quoted context omitted.

There is also Quarto, which I have had a good experience with: https://quarto.org/

I'm more excited about https://typst.app/

Quarto can output to Typst (as well as many other outputs simultaneously, e.g. .docx, HTML, PDF, PPT, etc) for it's typesetting capabilities. https://quarto.org/docs/output-formats/typst.html

Re: Big Book of R

#35

Post by malshe »

countrymile wrote: post #22
haberman wrote: post #14

Earlier quoted context omitted.

There is also Quarto, which I have had a good experience with: https://quarto.org/

R is beautiful for writing data rich books and websites. I started with rmarkdown but believe that most of the new developments are now in quarto?

Yes, that's correct. Quarto is language agnostic and Posit has chosen that route over just being an R shop.

Re: Big Book of R

#36

Post by malshe »

kingkongjaffa wrote: post #9

What is the best way to integrate some R code with a python backend? I’ve been tempted to port to python, but some of the stats libraries have no good counterparts, so, is there a ergonomic way to do this?

One of my students codes exclusively in Python. But in most cases newer econometrics methods are implemented in R first. So he just uses rpy2 to call R from his Python code. It works great. For example, recently he performed Bayesian synthetic control using the R code shared by the authors. It required stan backend but everything worked.

Re: Big Book of R

#37

Post by cye131 »

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.

Re: Big Book of R

#38

Post by kasperset »

cye131 wrote: post #37

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.

I love R and dplyr. It is very readable and easy to explain to non-programmers. I use it almost everyday. Not exactly on the topic,I am having difficulties debugging it. May be I need to brush up on debugging R. Not sure if there is a easy way to add breakpoint when using vscode.

Re: Big Book of R

#39

Post by JackeJR »

kasperset wrote: post #38
cye131 wrote: post #37

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.

I love R and dplyr. It is very readable and easy to explain to non-programmers. I use it almost everyday. Not exactly on the topic,I am having difficulties debugging it. May be I need to brush up on debugging R. Not sure if there is a easy way to add breakpoint when using vscode.

browser() ?

Re: Big Book of R

#40

Post by wwweston »

cye131 wrote: post #37

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.

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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