On Mon, May 21, 2012 at 2:00 AM, peter dalgaard <pda...@gmail.com> wrote:
[snip]
> What the poster probably wanted was something in the vein of
>
>> nm <- colnames(airquality)[1]
>> ff <- formula(bquote(.(as.name(nm))~Month))
>> aggregate(ff, airquality, mean, na.rm=T)
> Month Ozone
> 1 5 23.61538
> 2 6 29.44444
> 3 7 59.11538
> 4 8 59.96154
> 5 9 31.44828
or perhaps to use an implicit loop (since looping seemed to be part of it all):
results <- lapply(c("Ozone", "Solar.R"), function(n) {
aggregate(. ~ Month, airquality[, c(n, "Month")], mean, na.rm = TRUE)
})
## print results
results
## untested code based on OPs original example
vars <- colnames(df)[c(10,12,16,18,20,21,24:29,45)]
results <- lapply(vars, function(n) {
aggregate(. ~ x1 + x2 + x3, df[, c(n, "x1", "x2", "x3")], mean, na.rm = TRUE)
})
## print results
results
Cheers,
Josh
> --
> Peter Dalgaard, Professor
> Center for Statistics, Copenhagen Business School
> Solbjerg Plads 3, 2000 Frederiksberg, Denmark
> Phone: (+45)38153501
> Email: pd....@cbs.dk Priv: pda...@gmail.com
>
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--
Joshua Wiley
Ph.D. Student, Health Psychology
Programmer Analyst II, Statistical Consulting Group
University of California, Los Angeles
https://joshuawiley.com/
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