![]() Once your have some R code that runs, if you want to create a markdown report from it, it’s very easy with spin. The big benefit here, again, is not just saving the time in writing the Rmd, but the fact that you now have only one copy of your code that you need to maintain. It’s as if spin is saving you the step of going from R to Rmd. With spin, your original R source code is being converted into Rmd and then into a final report format automatically. Having to manage only one source as opposed to keeping two in sync makes my life much simpler. What if next week I want to change a parameter? I’d have to remember to make the exact same change in both the R source code and the Rmd file, so that the report will still match the R script. The problem is that now, because my code is in two places, I have a lot more work to maintain the code. I’m breaking the DRY principle (Don’t Repeat Yourself). The main thing to note here is that my whole analysis is now duplicated in two files: in the original R file as regular code, and in the Rmd file as code chunks. ![]() Repeat the above several times until the final.Rmd file, add text with formatting, surround code in code chunks Once my R code is ready, polish the code and make sure it runs smoothly when sourced.Write a bunch of interactive statements in an.There are many usecases to R markdown - whether it be showing the output from a homework assignment, a report to show a peer about your data, or just a report for yourself to more easily see and store results - and a common workflow is this: I’ve noticed a problem with the common approach that I adapted (and I know my colleagues use a similar approach) when creating R markdown (. Any line beginning with #+ is parsed as code chunk options.Any line beginning with #' is treated as a markdown directive ( #' # title will be a header, #' some **bold** text results in some bold text).Using spin to turn your R script into markdown output is very simple: I’m also going to talk only about the Rmd/md formats and not about any Sweave/LaTeX/HTML for simplicity. This might not sound like a big deal, but it has some important advantages that I’ll describe soon.ĭisclaimer: I may have a simplistic and non-comprehensive view of spin and knit knit certainly has many features that I’ve yet to explore. R), while knit requires a literate programming file (. ![]() The difference lies in the input: spin operates on R scripts (. In short: knitr::spin is similar to knitr::knit in that it takes as input a file with R code + formatting + text and produces a nice readable report, such as an HTML or markdown document. ![]() But not many people seem to know about knit’s awesome cousin - spin. Anyone who loves the idea of dynamic report generation with R is probably a big fan of knitr and its flagship function - knit. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |