Frank E Harrell Jr <fharrell@virginia.edu> wrote:
> What is the most efficient method for creating a data frame containing
> vectors of
> summary statistics? For example, suppose that data frame d contains
> age.group, sex, and y.
> I want to make a new data frame containing the combinations of age.group and
> sex
> that occurred in the data, along with a new matrix variable or two new
> variables containing
> the 0.25 and 0.75 quantiles. Then I'll pass the new summary data frame to
> trellis for
> graphing results. tapply will do the calculations I need but the resulting
> format is a
> matrix rather than a data frame containing combinations of stratification
> variables.
If I understand the question, I think you just need to convert
the matrix to an equivalent data frame. I use my function
'dfify' (which is short for data-frame-ify). It's a wrapper
around expand.grid() that converts a matrix (or multi-way array)
to an equivalent and nicely named data frame:
"dfify" <- function(arr, value.name="value", dn.names=names(dimnames(arr))) {
dn <- dimnames(arr <- as.array(arr))
if ( is.null(dn) ) stop("Can't data-frame-ify an array without dimnames")
names(dn) <- dn.names
ans <- cbind(expand.grid(dn), as.vector(arr))
names(ans)[ncol(ans)] <- value.name
ans
}
e.g.,
x <- cbind(1:3, 4:6)
dimnames(x) <- list(animal=c("dog", "cat", "pig"),
sex=c("male", "female")
)
print(x)
male female
dog 1 4
cat 2 5
pig 3 6
print(dfify(x, value.name="number"))
animal sex number
1 dog male 1
2 cat male 2
3 pig male 3
4 dog female 4
5 cat female 5
6 pig female 6
--Todd
--
Z. Todd Taylor
Pacific Northwest National Laboratory
Todd.Taylor@pnl.gov
Why do you drive on a parkway and park on a driveway?
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