(This article was first published on theBioBucket*, and kindly contributed to R-bloggers)
On Stackoverflow I found this useful example on how to apply custom statistics on a dataframe and return the results as list or dataframe:somedata<- 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$pct)
results <- c(f,w,m)
names(results) <- c("coef","sdev", "minPct")
results
}
# summary statistics as list with by():
by(somedata, list(country=somedata$country), someStats)
# ..or as dataframe with ddply():
library(plyr)
ddply(somedata, .(country), someStats)
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