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While not huge, they can be previewed in RStudio (not sure if IPN/Jupyter can be) but generally it's not a bad idea to have all the tooling from the same langua
by kriro 10y ago
While not huge, they can be previewed in RStudio (not sure if IPN/Jupyter can be) but generally it's not a bad idea to have all the tooling from the same language crowd (imo). Worst case it's an extra alternative to the excellent IPN/Jupyter.
I've used RStudio more and more for my "quick check stats" like quickly calculating interrater reliability or whatever pops up (I only know the basics of R). As such I can totally see myself quickly sharing things with R Notebooks.
For everything that requires "plumbing" and/or actually uses stats in software I gravitate towards the Python toolchain. Might not make sense but that's how I work. I've also noticed that RStudio is accessible enough to non programmers for the same quick checks I run (converting over some SPSS users...yay?!).
- baldfat 10y agoFrom kintr website: http://yihui.name/knitr/demo/engines/ http://yihui.name/knitr/demo/engines/ Language wise you can use the following in knitr: We can use any languages in knitr, including but not limited to R. Here are some simple demos with Python, Awk, Ruby, Haskell, Bash, Perl, Graphviz, TikZ, SAS, Scala, and CoffeeScript, etc: python.Rmd (output) c.Rmd (output) fortran.Rmd (output) sql.Rmd (output) awk.Rmd (output) ruby.Rmd (output) haskell.Rmd (output) bash.Rmd (output) perl.Rmd (output) dot.Rmd (output) tikz.Rmd (output) sas.Rmd (output) coffeescript.Rmd (output) polyglot.Rmd (output) Scala, Python, and Bash Also glad Python works for you and it is an awesome choice. I would just recommend looking at dplyr tutorial for the "plumbing." you might keep to your Python but this is an awesome workflow. https://cran.rstudio.com/web/packages/dplyr/vignettes/introduction.html https://cran.rstudio.com/web/packages/dplyr/vignettes/introd...
- claytonjy 10y agoOne drawback worth mentioning is that while all R chunks in a notebook share the same environment, non-R chunks do not. This means that if the first e.g. python chunk creates a variable `x`, the next python chunk will not be able to use it. Jupyter notebooks don't have this issue.