Hello,
I have a problem which has bitten me occasionally. I often need to
prepare graphs for many variables in a data set, but seldom for all.
or for any large number of sequential or sequentially named variables.
Often I need several graphs for different subsets of the dataset
for a given variable. I run into similar problems with other needs
besides graphing.
What I would like to do is something like "write a function which
takes the *name* of a variable, presumably a s a character string,
from a dataframe, as one argument, and the dataframe, as a second argument".
For example, where y is to be the the name of a variable in a given
dataframe d, and the other variables needed, T, M and so on, are
to be found in the same dataframe :-
pf <- function (y,data,...) {
p1 <- xyplot(y~x|T,data)
p2 <- xyplot(y~x|T,subset(data,M == 2))
p3 <- xyplot(y~x|T,subset(data,M == 4))
#print(p1,p2,p3....)
}
pf(Score1,data)
pf(Score2,data)
This fails, because, of course, Score 1, Score 2 etc.. are not
defined, or if you pass them as pf(data$Score2,data), then when you
subset the
data, data$Score2 is now the wrong shape.
I've come up with various
inelegant hacks, (often with for loops), for getting around this over
the
last few years, but I can't help feeling that I'm missing something
obvious, which I've been too dim to spot.
Depending on your needs (e.g., you use formulas, which can be trickier),
I think I often do something like:
# I prefer this, I quote the variable name...
df1 <- data.frame(x = rnorm(100),
score1 = rnorm(100),
M = sample(c(2, 4), 100, replace = TRUE))
pf <- function (y,data,...) {
data$y <- data[[y]]
xyplot(y~x, subset(data, M == 2))
}
pf("score1", df1)
# as an alternative, use eval/substitute, don't have to quote
pf2 <- function (y,data,...) {
data$y <- eval(substitute(y), data)
xyplot(y~x, subset(data, M == 2))
}
pf2(score1, df1)
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