OK. It seems that a clear consensus exists for the excision of R _proprio 
dictu_ from Sage.

If we break it, can we at least keep the (Sage's) pieces ? An optional 
package offering the current R interface(s) depending  on a systemwide(at 
least user-reachable) version of R and the R library might offer the 
functionality without entailing the (not so trivial) work of maintaining 
our own R port.

Do you have an idea of the amount of work involved ? And how to, do it ? 
The rpy2 part is probably easy, but I expect surprises on the pexpec(t) 
front (at least if we want to keep compatibility with existing code using 
current R interface facilities...).  Any hint on the right starting 
point(s) would be welcome...

BTW : I have also had a (quite superficial) look at what pandas and 
statsmodel claim to do. They (and scikit-learn, which look interesting, and 
stan, already available from Python) might be indeed useful for 
run-of-the-mill descriptive analysis and regression models (and Stan for 
more exotic modeling). Packaging them for Sage might prove useful.

However, those 9000+ R packages are here for a reason : if some of them (a 
small minority, IMHO) are obvious PhD-earning byproducts, others aim to 
solve difficult (if specialized) problems, badly solved (or not even 
considered) by the aforementioned trio. keeping a way to reach them from 
Sage might be important. Hence my plea for an "R interface(s)" package.

Another (IMHO futile) reason for keeping an R interface in our arsenal is 
"name recognition" : quoting R in a "Materials and methods" section no 
longer raises questions from reviewers ; somehow, I doubt that pandas and 
statmodels get the same answer...

What can you add ? Can someone propose a work plan ?

--
Emmanuel Charpentier

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