Take the 2-minute tour ×  Much has been written here about
developing a workflow in R for statistical projects. The most
popular workflow seems to be Josh Reich's LCFD model. With a
main.R containing code:   so that a single source('main.R') runs
the entire project.  Q: Is there a reason to prefer this
workflow to one in which the line-by-line interpretive work done
in load.R, clean.R, and do.R is replaced by functions which are
called by main.R?  I can't find the link now, but I had read
somewhere on SO that when programming in R one must get over
their desire to write everything in terms of function calls---
that R was MEANT to be written is this line-by-line interpretive
form.  Q: Really? Why?  I've been frustrated with the LCFD
approach and am going to probably write everything in terms of
function calls. But before doing this, I'd like to hear from the
good folks of SO as to whether this is a good idea or not.
EDIT: The project I'm working on right now is to (1) read in a
set of financial data, (2) clean