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Why Clinical Laboratorians Should Embrace the R Programming Language

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Re: Why Clinical Laboratorians Should Embrace the R Programming Language

#11

Post by refactor_master »

To me, R seems more like a cobbled together ecosystem of automation within statistics, rather than an actual language.

Compared with Python the language ergonomics of R are confusing and inconsistent.

I guess momentum and establishment is also a feature in itself though I’ve personally never felt that, one of the selling points, the esoteric statistics packages at the edge would be of any use to me.

The use I’ve seen is reminiscent of Spyder and Notebooks: tangled, unreadable mess of line-by-line execution where people are prone to re-running stuff out of order.

Re: Why Clinical Laboratorians Should Embrace the R Programming Language

#14

Post by akg_67 »

refactor_master wrote: post #11

To me, R seems more like a cobbled together ecosystem of automation within statistics, rather than an actual language. Compared with Python the language ergonomics of R are confusing and inconsistent. I guess momentum and establishment is also a feature in itself though I’ve personally never felt that, one of the selling points, the esoteric statistics packages at the edge would be of any use to me. The use I’ve seen…

Actually, it most probably reverse. Python, numpy, pandas, etc are cobbled together with duct tape to do what R does elegantly. There is no consistency with Python ecosystem.

Re: Why Clinical Laboratorians Should Embrace the R Programming Language

#16

Post by ekianjo »

ppod wrote: post #9

There are some specific advantages that R has over other languages in this context. One is that you can use (almost)* a single source document to produce docx, pdf, and interactive html output. * I can't quite get htmlwidgets and docx formats to work together in bookdown without using separate commands for the interactive tables (DT and flextable).

Rmarkdown is certainly a big win in terms of reporting and its integration with Rstudio makes it a breeze to work with it

Re: Why Clinical Laboratorians Should Embrace the R Programming Language

#17

Post by nabla9 »

tomrod wrote: post #10
nabla9 wrote: post #4

Earlier quoted context omitted.

I think that R libraries have edge over Python and Julia in quality and quantity. If you like to write lots of code, Python might be better. But if you use it in clinical research, R has probably better packages for whatever you need.

R packages are the wild west as far as code quality goes. In one corner you have Hadley Wickam producing phenomenal efforts like tidyverse and ggplot. In the other corner you have a herd of feral cats. Python gets scrutiny but most packages are on github and feedback can be received. Although, you should read the source code regardless. EDIT: And I re-emphasize -- never trust the source code, even if the company you…

There are different qualities. Code quality and quality of the functionality.

In R you more packages that do what you expect (mathematically) but the implementation is inelegant and slow. Written by someone who knows exactly what they need and what the package should do, but has difficulty of writing it down.

In python you many well implemented neat packages where the code is well implemented and performs well, but is not exactly doing what user need or skips important features because they are conceptually difficult.

Re: Why Clinical Laboratorians Should Embrace the R Programming Language

#18

Post by ekianjo »

teruakohatu wrote: post #3

I would say you could replace R with Python or Julia and do just fine. Anything must be better than SPSS. That said, R had come a long way in recent years and is enjoyable to use. It is very complete as far as statistics go.

R has much better syntax with tidyverse for data wrangling and even up to models with tidymodels and all. Python in comparison is hard to read.

Re: Why Clinical Laboratorians Should Embrace the R Programming Language

#19

Post by z77dj3kl »

ekianjo wrote: post #18
teruakohatu wrote: post #3

I would say you could replace R with Python or Julia and do just fine. Anything must be better than SPSS. That said, R had come a long way in recent years and is enjoyable to use. It is very complete as far as statistics go.

R has much better syntax with tidyverse for data wrangling and even up to models with tidymodels and all. Python in comparison is hard to read.

What... Have you seen the piping syntax in tidyverse? It's incomprehensible unless you put in a lot of effort to understand all that's going on.

Re: Why Clinical Laboratorians Should Embrace the R Programming Language

#20

Post by CalRobert »

R might be a perfectly fine language, but the culture and ecosystem around R seem to produce a lot of untested, difficult to read code. Globals everywhere, mediocre requirements resolution, and a lack of forced namespacing come to mind. Maybe it's a result of being used by people who are not primarily programmers.
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