similar to: Variable/function namespaces WAS: Bug in subsetting data frame (PR#13515)

I've read in many places that R semantics are based on Scheme semantics. As a long-time Lisp user and implementor, I've tried to make this more precise, and this is what I've found so far. I've excluded trivial things that aren't basic semantic issues: support for arbitrary-precision integers; subscripting; general style; etc. I would appreciate corrections or additions from

Tested in R 2.8.1 Windows > ff <- formals(function(x)1) > ff1 <- as.list(function(x)1)[1] # ff1 acts the same as ff in the examples below, but is a list rather than a pairlist > dput( ff , control=c("warnIncomplete")) list(x = ) This string is not parsable, but dput does not give a warning as specified. > dput( ff ,

To test two environments for object equality (Lisp EQ), I can use 'identity': > e1 <- environment(local(function()x)) > e2 <- environment(local(function()x)) > identical(e1,e2) # compares object identity [1] FALSE > identical(as.list(e1),as.list(e2)) # compares values as name->value mapping [1] TRUE # (is there a

Following Duncan's suggestion, I forward the below to R-devel. vQ -------- Original Message -------- Subject: Re: [R] Randomly remove condition-selected rows from a matrix Date: Fri, 02 Jan 2009 10:34:52 -0500 From: Duncan Murdoch <murdoch at stats.uwo.ca> To: Wacek Kusnierczyk <Waclaw.Marcin.Kusnierczyk at idi.ntnu.no> CC: R help <R-help at stat.math.ethz.ch>

I would like to trace functions, displaying their arguments and return value, but I haven't been able to figure out how to do this with the 'trace' function. After some thrashing, I got as far as this: fact <- function(x) if(x<1) 1 else x*fact(x-1) tracefnc <- function() dput(as.list(parent.frame()), # parent.frame() holds arg list

I would like to trace functions, displaying their arguments and return value, but I haven't been able to figure out how to do this with the 'trace' function. After some thrashing, I got as far as this: fact <- function(x) if(x<1) 1 else x*fact(x-1) tracefnc <- function() dput(as.list(parent.frame()), # parent.frame() holds arg list

I'm new to R and very excited about its possibilities. But I'm struggling with some very simple things, probably because I haven't found the correct documentation. Here's a simple example which illustrates several of my problems. Suppose I want to have a regexp match against a string, and return all the matching substrings in a vector of strings. regexp <-

Even using the VBA back of Excel to create interfaces with R would make a lot of sense. Suppose I could have access to VBA macros that import and export data into R , it would be great. The R GUI series like Rattle come even closer to Excel...so a VBA _R_ExCel package might be useful to ordinary folks . Besides Excel costs money, so adding R functions to Open Office would help both of them ( if

I have two vectors, a and b. b is a text file. I want to find in b those elements of a which occur at the beginning of the line in b. I have the following code, but it only returns a value for the first value in a, but I want both. Any ideas please. a = c(2,3) b = NULL b[1] = "aaa 2 aaa" b[2] = "2 aaa" b[3] = "3 aaa" b[4] = "aaa 3 aaa"

Is there a pretty-printer for R data (and code for that matter), similar to Lisp's prettyprint/grind? I've looked in CRAN, and couldn't find anything. For example, I'd like to have: prettyprint(list(a=1:20*2, b=list(data.frame(q = c(2,1,3), r = c(3,1,2), s = c(1,3,2)), as.POSIXct("2014-02-03"))) * =>* list(a = c(2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22,

I recently traced a bug of mine to the fact that cumsum(s)[length(s)] is not always exactly equal to sum(s). For example, x<-1/(12:14) sum(x) - cumsum(x)[3] => 2.8e-17 Floating-point addition is of course not exact, and in particular is not associative, so there are various possible reasons for this. Perhaps sum uses clever summing tricks to get more accurate results? In some

Tested in: R version 2.8.1 (2008-12-22) / Windows Recursive default argument references normally give nice clear errors. In the first set of examples, you get the error: Error in ... : promise already under evaluation: recursive default argument reference or earlier problems? (function(a = a) a ) () (function(a = a) c(a) ) () (function(a = a) a[1] ) () (function(a = a)

Function factor() in the current development version (2009-05-22) guarantees that levels are different character strings. However, they may represent the same decimal number. The following example is derived from a posting by Stavros Macrakis in thread "Match .3 in a sequence" in March nums <- 0.3 + 2e-16 * c(-2,-1,1,2) f <- factor(nums) levels(f) # [1]

What is the recommended class for time of day (independent of calendar date)? And what is the recommended way to get the time of day from a POSIXct object? (Not a string representation, but a computable representation.) I have looked in the man page for DateTimeClasses, in the Time Series Analysis Task View and in Spector's Data Manipulation book but haven't found these. Clearly I can

What is the 'idiomatic' way of writing a vectorized switch statement? That is, I would like to write, e.g., vswitch( c('a','x','b','a'), a= 1:4, b=11:14, 100 ) => c(1, 100, 13, 4 ) equivalent to ifelse( c('a','x','b','a') ==

I was surprised to find that df$a[1] is an order of magnitude faster than df[1,"a"]: > df <- data.frame(a=1:10) > system.time(replicate(100000, df$a[3])) user system elapsed 0.36 0.00 0.36 > system.time(replicate(100000, df[3,"a"])) user system elapsed 4.09 0.00 4.09 A priori, I'd have thought that combining the row and column

Judging from the traffic on this mailing list, a lot of R beginners are trying to write things like assign( paste( "myvar", i), ...) where they really should probably be writing myvar[i] <- ... Do we have any idea where this bizarre habit comes from? -s

I was wondering what the criteria were for including books on the Books Related to R page <http://www.r-project.org/doc/bib/R-books.html>. (There is no maintainer listed on this page.) In particular, I was wondering why the following two books are not listed: * Andrew Gelman, Jennifer Hill, *Data Analysis Using Regression and Multilevel/Hierarchical Models*. (CRAN package 'arm') *

NOTA BENE: This email is about `=`, the assignment operator (e.g. {a=1} which is equivalent to { `=`(a,1) } ), not `=` the named-argument syntax (e.g. f(a=1), which is equivalent to eval(structure(quote(f(1)),names=c('','a'))). As far as I can tell from the documentation, assignment with = is precisely equivalent to assignment with <-. Yet they call different primitives: >

NOTA BENE: This email is about `=`, the assignment operator (e.g. {a=1} which is equivalent to { `=`(a,1) } ), not `=` the named-argument syntax (e.g. f(a=1), which is equivalent to eval(structure(quote(f(1)),names=c('','a'))). As far as I can tell from the documentation, assignment with = is precisely equivalent to assignment with <-. Yet they call different primitives: >