使用每个()与reshape2 :: dcast聚合数据

我通常使用reshape包来聚合一些数据(呃),通常用plyr,因为每个都有超级棒的功能.最近,我收到了一个建议,切换到reshape2并尝试一下,现在我似乎无法再使用每个魔法.

重塑

> m <- melt(mtcars, id.vars = c("am", "vs"), measure.vars = "hp")
> cast(m, am + vs ~ variable, each(min, max, mean, sd))
  am vs hp_min hp_max   hp_mean    hp_sd
1  0  0    150    245 194.16667 33.35984
2  0  1     62    123 102.14286 20.93186
3  1  0     91    335 180.83333 98.81582
4  1  1     52    113  80.57143 24.14441

reshape2

require(plyr)
> m <- melt(mtcars, id.vars = c("am", "vs"), measure.vars = "hp")
> dcast(m, am + vs ~ variable, each(min, max, mean, sd))
Error in structure(ordered, dim = ns) : 
  dims [product 4] do not match the length of object [16]
In addition: Warning messages:
1: In fs[[i]](x, ...) : no non-missing arguments to min; returning Inf
2: In fs[[i]](x, ...) : no non-missing arguments to max; returning -Inf

我没有心情去梳理它,因为我之前的代码就像一个重塑的魅力,但我真的很想知道：

>是否有可能与dcast一起使用？
>是否建议使用reshape2？重塑已弃用？

你的第一个问题的答案似乎是否定的.引自？reshape2 ::: dcast：

If the combination of variables you supply does not uniquely identify
one row in the original data set, you will need to supply an
aggregating function, fun.aggregate. This function should take a
vector of numbers and return a single summary statistic.

看看Hadley的reshape2的github页面表明他知道这个功能被删除了,但似乎认为在plyr中做得更好,大概是这样的：

ddply(m,.(am,vs),summarise,min = min(value),
                           max = max(value),
                           mean = mean(value),
                           sd = sd(value))

或者如果你真的想继续使用每个：

ddply(m,.(am,vs),function(x){each(min,max,mean,sd)(x$value)})