I wrote a wrapper around ftable
because I need to compute flat tables with frequency and percentage for many variables:
mytable <- function(...) {
tab <- ftable(...,
exclude = NULL)
prop <- prop.table(x = tab,
margin = 2) * 100
bind <- cbind(as.matrix(x = tab),
as.matrix(x = prop))
margin <- addmargins(A = bind,
margin = 1)
round(x = margin,
digits = 1)
}
mytable(formula = wool + tension ~ breaks,
data = warpbreaks)
A_L A_M A_H B_L B_M B_H A_L A_M A_H B_L B_M B_H
10 0 0 1 0 0 0 0.0 0.0 11.1 0.0 0.0 0.0
12 0 1 0 0 0 0 0.0 11.1 0.0 0.0 0.0 0.0
13 0 0 0 0 0 1 0.0 0.0 0.0 0.0 0.0 11.1
14 0 0 0 1 0 0 0.0 0.0 0.0 11.1 0.0 0.0
15 0 0 1 0 0 2 0.0 0.0 11.1 0.0 0.0 22.2
...
Sum 9 9 9 9 9 9 100.0 100.0 100.0 100.0 100.0 100.0
However, I can not use the subset argument from ftable
with my function, nor with the minimal mytable <- function(...) ftable(...)
:
mytable(formula = wool + tension ~ breaks,
data = warpbreaks,
subset = breaks < 20)
Error in eval(substitute(subset), data, env) :
..3 used in an incorrect context, no ... to look in
I know I can subset in the data argument with data = warpbreaks[warpbreaks$breaks < 20, ]
as a workaround, but I am looking to improve my knowledge of R. "Advanced R" helped me to understand that the error is due to non-standard evaluation, but I did not manage to correct my code.
So my questions are:
breaks
in warpbreaks
?mytable(x = warpbreaks$tension, row.vars = 1)
.)With a function definition without ...
, I get a different error:
mytable <- function(formula,
data,
subset) ftable(formula = formula,
data = data,
subset = subset)
mytable(formula = wool + tension ~ breaks,
data = warpbreaks,
subset = breaks < 20)
Error in xj[i] : invalid subscript type 'closure'
This error led me to ressources I havent found before.
# function 1
mytable <- function(...) {
mc <- match.call()
mc["exclude"] <- list(NULL)
do.call(what = ftable,
args = as.list(x = mc[-1]))
#etc
}
The write.csv
family and lm
source code led me to:
# function 2
mytable <- function(...) {
mc <- match.call()
mc[[1]] <- quote(expr = ftable)
mc["exclude"] <- list(NULL)
eval(expr = mc)
# etc
}
However, I am looking for pro and cons of both methods (function 1 and function 2), because I do not know if a method is to be favored. So far I just found that do.call
might be slower.
More importantly, these methods led my to another issue: I can not use my wrapper with lapply
and with
anymore.