Don't use argument abbreviations.

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: tables
 Title: Formula-Driven Table Generation
-Version: 0.9.28
+Version: 0.9.29
 Author: Duncan Murdoch
 Description: Computes and displays complex tables of summary statistics.
   Output may be in LaTeX, HTML, plain text, or an R

NEWS.md

@@ -1,3 +1,9 @@
+# tables 0.9.29
+
+- In a few places `len` was used instead of `length.out` in calls to
+`rep()`, leading to warnings.  Similarly, `rep` was used instead of 
+`replace` in `sample()` (issue #28).
+
 # tables 0.9.28
 
 - A factor level of `""` caused an error when displayed.  It will

R/tabular.R

@@ -706,14 +706,14 @@ tabular.formula <- function(table, data=NULL, n, suppressLabels=0, ...) {
 }
 
 justify <- function(x, justification="c", width=max(nchar(x))) {
-    justification <- rep(justification, len=length(x))
+    justification <- rep(justification, length.out = length(x))
     change <- justification %in% c("c", "l", "r")
     if (!any(change)) return(x)
     y <- x[change]
     justification <- justification[change]
     y <- sub("^ *", "", y)
     y <- sub(" *$", "", y)
-    width <- rep(width, len=length(x))
+    width <- rep(width, length.out = length(x))
     width <- width[change]
     lens <- nchar(y)
     ind <- justification == "c"

README.Rmd

@@ -55,7 +55,7 @@ set.seed(123)
 table_options(htmloptions(head=FALSE))
 
 X <- rnorm(125, sd=100)
-Group <- factor(sample(letters[1:5], 125, rep=TRUE))
+Group <- factor(sample(letters[1:5], 125, replace = TRUE))
 tab <- tabular( Group ~ 
                   (N=1) +
                   Format(digits=2)*X*

README.md

@@ -45,7 +45,7 @@ set.seed(123)
 table_options(htmloptions(head=FALSE))
 
 X <- rnorm(125, sd=100)
-Group <- factor(sample(letters[1:5], 125, rep=TRUE))
+Group <- factor(sample(letters[1:5], 125, replace = TRUE))
 tab <- tabular( Group ~ 
                   (N=1) +
                   Format(digits=2)*X*

man/Percent.Rd

@@ -72,9 +72,9 @@ in the \code{denom} argument to \code{Percent}.
 \seealso{\code{\link{Arguments}} for a different way to specify
 a multiple argument analysis function.}
 \examples{
-x <- factor(sample(LETTERS[1:2], 1000, rep=TRUE))
-y <- factor(sample(letters[3:4], 1000, rep=TRUE))
-z <- factor(sample(LETTERS[5:6], 1000, rep=TRUE))
+x <- factor(sample(LETTERS[1:2], 1000, replace = TRUE))
+y <- factor(sample(letters[3:4], 1000, replace = TRUE))
+z <- factor(sample(LETTERS[5:6], 1000, replace = TRUE))
 
 # These both do the same thing:
 tabular( (x + 1)*(y + 1) ~ (z + 1)*(1+(RowPct=Percent("row"))))

man/html.tabular.Rd

@@ -76,7 +76,7 @@ invisibly.
 \examples{
 \donttest{
 X <- rnorm(125, sd=100)
-Group <- factor(sample(letters[1:5], 125, rep=TRUE))
+Group <- factor(sample(letters[1:5], 125, replace = TRUE))
 
 tab <- tabular( Group ~ (N=1)+Format(digits=2)*X*((Mean=mean) + Heading("Std Dev")*sd) )
 

man/matrix_form.tabular.Rd

@@ -26,8 +26,8 @@ Duncan Murdoch with help from Gabe Becker.
 }
 \examples{
 if (requireNamespace("formatters")) {
-  Sex <- factor(sample(c("Male", "Female"), 100, rep=TRUE))
-  Status <- factor(sample(c("low", "medium", "high"), 100, rep=TRUE))
+  Sex <- factor(sample(c("Male", "Female"), 100, replace = TRUE))
+  Status <- factor(sample(c("low", "medium", "high"), 100, replace = TRUE))
   z <- rnorm(100) + 5
   fmt <- function(x) {
   s <- format(x, digits=2)

man/tabular.Rd

@@ -226,8 +226,8 @@ tabular( (Species + 1) ~ (n=1) + Format(digits=2)*
          (Sepal.Length + Sepal.Width)*(mean + sd), data=iris )
 
 # This example shows some of the less common options         
-Sex <- factor(sample(c("Male", "Female"), 100, rep=TRUE))
-Status <- factor(sample(c("low", "medium", "high"), 100, rep=TRUE))
+Sex <- factor(sample(c("Male", "Female"), 100, replace = TRUE))
+Status <- factor(sample(c("low", "medium", "high"), 100, replace = TRUE))
 z <- rnorm(100)+5
 fmt <- function(x) {
   s <- format(x, digits=2)

vignettes/HTML.Rmd

@@ -31,7 +31,7 @@ library(tables)
 The table is now constructed in the usual way.  
 ```{r}
 X <- rnorm(125, sd=100)
-Group <- factor(sample(letters[1:5], 125, rep=TRUE))
+Group <- factor(sample(letters[1:5], 125, replace = TRUE))
 tab <- tabular( Group ~ (N=1)+Format(digits=2)*X*((Mean=mean) + Heading("Std Dev")*sd) )
 ```
 In an R Markdown document, you don't want each table

vignettes/knitrTables.Rmd

@@ -144,7 +144,7 @@ For the examples below we use the following definitions:
 set.seed(100)
 X <- rnorm(10)
 X
-A <- sample(letters[1:2], 10, rep=TRUE)
+A <- sample(letters[1:2], 10, replace = TRUE)
 A
 F <- factor(A)
 F
@@ -1207,8 +1207,8 @@ yield ugly NA and NaN statistics:
 
 ```{r}
 set.seed(1206)
-q <- data.frame(p = rep(c("A","B"),each=10,len=30),
-                           a = rep(c(1,2,3),each=10),id=seq(30),
+q <- data.frame(p = rep(c("A","B"), each = 10, length.out = 30),
+                           a = rep(c(1,2,3),each = 10),id = seq(30),
                            b = round(runif(30,10,20)),
                            c = round(runif(30,40,70)),
 		stringsAsFactors = FALSE)

vignettes/tables.Rnw

@@ -148,7 +148,7 @@ For the examples below we use the following definitions:
 set.seed(100)
 X <- rnorm(10)
 X
-A <- sample(letters[1:2], 10, rep=TRUE)
+A <- sample(letters[1:2], 10, replace = TRUE)
 A
 F <- factor(A)
 F
@@ -1238,7 +1238,7 @@ yield ugly NA and NaN statistics:
 \begin{center}
 <<results=tex>>=
 set.seed(1206)
-q <- data.frame(p = rep(c("A","B"),each=10,len=30),
+q <- data.frame(p = rep(c("A","B"), each = 10, length.out = 30),
                            a = rep(c(1,2,3),each=10),id=seq(30),
                            b = round(runif(30,10,20)),
                            c = round(runif(30,40,70)),

vignettes/tables.Rout.save

@@ -68,7 +68,7 @@ All  & $150$ & $5.84$ & $0.83$ & $3.06$ & $0.44$ \\
  [5]  0.11697127  0.31863009 -0.58179068  0.71453271
  [9] -0.82525943 -0.35986213
 
-> A <- sample(letters[1:2], 10, rep = TRUE)
+> A <- sample(letters[1:2], 10, replace = TRUE)
 
 > A
  [1] "b" "b" "b" "b" "a" "a" "b" "b" "b" "a"
@@ -861,9 +861,9 @@ All  & $4$ \\
 
 > set.seed(1206)
 
-> q <- data.frame(p = rep(c("A", "B"), each = 10, len = 30), 
+> q <- data.frame(p = rep(c("A", "B"), each = 10, length.out = 30), 
 +     a = rep(c(1, 2, 3), each = 10), id = seq(30), b = round(runif(30, 
-+         10, 2 .... [TRUNCATED] 
++        .... [TRUNCATED] 
 
 > tab <- tabular((Factor(p) * Factor(a) + 1) ~ (N = 1) + 
 +     (b + c) * (mean + sd), data = q)
@@ -983,4 +983,4 @@ All  & $150$ & $5.84$ & $0.83$ & $3.06$ & $0.44$ \\
  *** Run successfully completed ***
 > proc.time()
    user  system elapsed 
-  2.642   0.138   2.798 
+  0.688   0.030   0.718