Consider that I have the following data and function returning summary statistics that I like
landlines <- data.frame(
year=rep(c(1990,1995,2000,2005,2010),times=3),
country=rep(c("US", "Brazil", "Asia"), each=5),
pct = c(0.99, 0.99, 0.98, 0.05, 0.9,
0.4, 0.5, 0.55, 0.5, 0.45,
0.7, 0.85, 0.9, 0.85, 0.75)
)
someStats <- function(x)
{
dp <- as.matrix(x$pct)-mean(x$pct)
indp <- as.matrix(x$year)-mean(x$year)
f <- lm.fit( indp,dp )$coefficients
w <- sd(x$pct)
m <- min(x$pct)
results <- c(f,w,m)
names(results) <- c("coef","sdev", "minPct")
results
}
I can apply that function to a data subset successfully like this:
> someStats(landlines[landlines$country=="US",])
coef sdev minPct
-0.022400 0.410938 0.050000
or look at a breakdown by country like this:
> by(landlines, list(country=landlines$country), someStats)
country: Asia
coef sdev minPct
0.00200000 0.08215838 0.70000000
---------------------------------------------------------------------------------------
country: Brazil
coef sdev minPct
0.00200000 0.05700877 0.40000000
---------------------------------------------------------------------------------------
country: US
coef sdev miPct
-0.022400 0.410938 0.050000
Trouble is, that is not the data.frame object I need for further processing, and it won’t cast as such:
> as.data.frame( by(landlines, list(country=landlines$country), someStats) )
Error in as.data.frame.default(by(landlines, list(country = landlines$country), :
cannot coerce class '"by"' into a data.frame
“No problem!” I think, since the similar aggregate() function does return a data.frame:
> aggregate(landlines$pct, by=list(country=landlines$country), min)
country x
1 Asia 0.70
2 Brazil 0.40
3 US 0.05
Trouble is, it doesn’t work properly with arbitrary functions:
> aggregate(landlines, by=list(country=landlines$country), someStats)
Error in x$pct : $ operator is invalid for atomic vectors
What I really want to get is a data.frame object with the following columns:
- country
- coef
- sdev
- minPct
How can I do that?
take a look at the
plyrpackage and in particularddplyIdeally your function explicitly returns a
data.framebut in this case, it can be coerced to one easily and correctly.