考虑到我有以下数据和函数返回我喜欢的汇总统计信息
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$pct)
results <- c(f,w,m)
names(results) <- c("coef","sdev", "minPct")
results
}
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我可以像这样成功地将该函数应用于数据子集:
> someStats(landlines[landlines$country=="US",])
coef sdev minPct
-0.022400 0.410938 0.050000
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或按国家/地区细分如下:
> by(landlines, list(country=landlines$country), someStats)
country: Asia
coef sdev minPct
0.00200000 0.08215838 0.70000000
---------------------------------------------------------------------------------------
country: Brazil
coef sdev minPct
0.00200000 0.05700877 0.40000000
---------------------------------------------------------------------------------------
country: US
coef sdev miPct
-0.022400 0.410938 0.050000
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问题是,这不是data.frame我需要进一步处理的对象,它不会这样转换:
> as.data.frame( by(landlines, list(country=landlines$country), someStats) )
Error in as.data.frame.default(by(landlines, list(country = landlines$country), :
cannot coerce class '"by"' into a data.frame
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“没问题!” 我认为,因为类似的aggregate()函数确实返回 a data.frame:
> aggregate(landlines$pct, by=list(country=landlines$country), min)
country x
1 Asia 0.70
2 Brazil 0.40
3 US 0.05
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问题是,它不能与任意函数一起正常工作:
> aggregate(landlines, by=list(country=landlines$country), someStats)
Error in x$pct : $ operator is invalid for atomic vectors
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我真正想要的是一个data.frame具有以下列的对象:
我怎样才能做到这一点?
看一下plyr包装,特别是ddply
> ddply(landlines, .(country), someStats)
country coef sdev minPct
1 Asia 0.0020 0.08215838 0.70
2 Brazil 0.0020 0.05700877 0.40
3 US -0.0224 0.41093795 0.05
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理想情况下,您的函数显式返回 a data.frame,但在这种情况下,它可以轻松且正确地强制为 1。