(I think) I have a pretty solid use case for using RMarkdown: I am analysing results of different simulation runs and basically have to repeatedly run the same codes to create the plots. I've started to create reports and like what RMarkdown can do but I am unsure on the best practice of data preparation. The simulation data I use is stored in different files that I first have to mix and match to get the plots and analyses I am looking for. Is it generally inadvisable to "do it all" in markdown?
Prepping the data and saving it in a new file that I would then use for the RMarkdown report probably makes sense regarding performance but for part of my workflow, I would again find myself re-running code.
A hint is greatly appreciated