计算每个群体的均值和方差无需编写循环,这里有一些方法
with(df, tapply(R, Population, function(x) c(mean(x), var(x))))
或者
aggregate(R ~ Population, df, function(x) c(mean(x), var(x)))
或者
do.call(rbind, by(df, df$Population, function(x) c(mean(x$R), var(x$R))))
或者
do.call(rbind, lapply(split(df, df$Population), function(x) c(mean(x$R), var(x$R))))
或者
library(data.table)
setDT(df)[, list(Var = var(R), Mean = mean(R)), by = Population]
或者
library(dplyr)
df %>%
group_by(Population) %>%
summarise(Var = var(R), Mean = mean(R))
如果你坚持要得到一个for
循环的解决方案,在这里不用
的预定义的结果数据集(因为它是一个不好的做法,在循环中不断增长的对象)
Res <- data.frame(Population = unique(df$Population),
Mean = rep(NA, length(unique(df$Population))),
Var = rep(NA, length(unique(df$Population))))
运行循环
for(i in unique(df$Population)){
Res$Mean[Res$Population == i] <- mean(df$R[df$Population == i])
Res$Var[Res$Population == i] <- var(df$R[df$Population == i])
}
Res
# Population Mean Var
# 1 Bari1 108.6685 375.0275
为什么你想用循环做到这一点?如果'df'是你的数据集,你可以试试'with(df,tapply(R,Population,function(x)c(mean(x),var(x))))''或者'聚合(R〜Population,df,function(x)c(mean(x),var(x)))' – 2014-11-04 18:10:36
它的工作原理非常感谢 – user3792077 2014-11-04 18:18:58
为什么要使用for循环? – 2014-11-04 18:22:48