From brahm@alum.mit.edu  Wed Oct  3 16:39:21 2001
From: brahm@alum.mit.edu (brahm@alum.mit.edu)
Date: Wed, 3 Oct 2001 17:39:21 +0200 (MET DST)
Subject: [Rd] Several R vs S-Plus issues (PR#1110)
Message-ID: <200110031539.RAA09399@pubhealth.ku.dk>

Hi, all,

   I've been converting code from S-Plus ("S" for short) to R for a few weeks.
Here are some differences I've found, aside from the big well-known ones
(scoping, models, data storage) and the contents of Kurt Hornik's FAQ section
3.3.3.  Let me start with the ones that seem like serious bugs or deficiencies:

1) LETTERS[c(NA,2)] in S is c("","B"), but in R is c("NA","B").

  This is TERRIBLE!  I have a ton of S-Plus code that looks like:
     y$ticker <- z$ticker[match(y$cusip, z$cusip)]
  and I count on a ticker of "" to indicate failed lookups.  Not only will
  I need to change all that code, but I'll never be able to trade Nabisco
  (ticker NA) again.  PLEASE re-consider this choice, or at least make it
  an option: option(na.char="").


2) system() has no "input" argument in R.

   Here's a (Unix) example:
   S> system("cd mydir; latex myfile", input="x")
     which goes to the directory where myfile lives and LaTeX's it, passing
     an "x" through STDIN in case LaTeX encounters an error.  My R fix is:
   R> system("cd mydir; echo x | latex myfile")
   Note that it's not as simple as  cmd <- paste("echo",input,"|",cmd).


3) R> myfun <- function(x, ...) {x[...] <- 0;  x}
   R> myfun(3)
   Error in myfun(3) : SubAssignArgs: invalid number of arguments

   It failed because no ... was given.  Fortunately, this is easily patched:
   R> myfun <- function(x, ...) {if (missing(...)) x[]<-0 else x[...]<-0; x}


4) Missing functions:
   a) identical() [scheduled for 1.4.0]
   b) slice.index()
   c) rowSums(), colSums(), colVars(), etc.
   d) unpaste() - R has strsplit, whose result is like the transpose of unpaste


5) rowsum() gives character dimnames in S, factor numbers in R.
   I've reported this early, and Brian D. Ripley promised a fix in 1.4.0.


OK, the rest are just differences, not complaints.  In fact, sometimes they are
very good differences.

1) Same argument given twice produces an error in R; S takes the last one.
   S> mean(x=4, x=5)    # Returns 5
   R> mean(x=4, x=5)    # Error

2) row.names(y) <- LETTERS[1:3] coerces list to dataframe in S, is error in R.

3) Default "what" for scan in S is "", in R is double(0).

4) Default "quote" for scan is "'\"" in R, causes different behavior than S.

5) which(<numeric>) converts to logical in S, is an error in R.

6) The NULL returned by if(F){...} is invisible in R, visible in S.

7) The NULL returned by return() is visible in R, invisible in S.

8) Args to "var" differ, and R has "cov".  S na.method="a" is like R use="p".

9) var (or cov) drops dimensions in S, not R.

10) cut allows labels=F in R, not in S (also left.include=T becomes right=F).

11) substring(s,"x") <- "X" only works in S, but R has s <- gsub("x","X",s).

12) S function casefold() replaced in R by toupper() or tolower().

13) Functions missing from S: sub(), gsub(), chartr(), toupper(), tolower()

14) Log scale indicated in S with par(xaxt)=="l", in R with par("xlog")==T.

			-- David Brahm (a215020@agate.fmr.com)

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[Rd] Several R vs S-Plus issues (PR#1110)
brahm@alum.mit.edu