Why aggregate() doesn't work here?
为什么aggregate()在这里不起作用?
> aggregate(cbind(var1 = 1:10, var2 = 101:110),
by=list(range=cut(1:10, breaks=c(2,4,8,10))),
FUN = function(x)
{
c(obs=length(x[, "var2"]), avg=mean(x[, "var2"]), sd=dev(x[, "var2"]))
})
Error in x[, "var2"] (from #1) : incorrect number of dimensions
> cbind(var1 = 1:10, var2 = 101:110)[, "var2"]
[1] 101 102 103 104 105 106 107 108 109 110
UPDATE
Returned aggregate() values after running the correct version:
运行正确的版本后返回的aggregate()值:
> r = aggregate(data.frame(var1 = 1:10, var2 = 101:110), by=list(range=cut(1:10, breaks=c(2,4,8,10))), FUN = function(x) { c(obs=length(x), avg=mean(x), sd=sd(x)) })
> class(r)
[1] "data.frame"
> dim(r)
[1] 3 3
> r[,1]
[1] (2,4] (4,8] (8,10]
Levels: (2,4] (4,8] (8,10]
> r[,2]
obs avg sd
[1,] 2 3.5 0.707107
[2,] 4 6.5 1.290994
[3,] 2 9.5 0.707107
> r[,3]
obs avg sd
[1,] 2 103.5 0.707107
[2,] 4 106.5 1.290994
[3,] 2 109.5 0.707107
> class(r[,2])
[1] "matrix"
> class(r[,3])
[1] "matrix"
2 个解决方案
#1
3
Supply a dataframe and understand that aggregate passes only column vectors so using x[ , "colname"] is doomed because "x" is not a dataframe:
提供数据帧并理解聚合只传递列向量,因此使用x [,“colname”]注定要失败,因为“x”不是数据帧:
aggregate(data.frame(var1 = 1:10, var2 = 101:110),
by=list(range=cut(1:10, breaks=c(2,4,8,10))),
FUN = function(x)
{
c(obs=length(x), avg=mean(x), sd=sd(x))
})
#------------
range var1.obs var1.avg var1.sd var2.obs var2.avg var2.sd
1 (2,4] 2.0000000 3.5000000 0.7071068 2.0000000 103.5000000 0.7071068
2 (4,8] 4.0000000 6.5000000 1.2909944 4.0000000 106.5000000 1.2909944
3 (8,10] 2.0000000 9.5000000 0.7071068 2.0000000 109.5000000 0.7071068
#2
3
That's because aggregate doesn't pass data.frames to its FUN= argument. It passes the vector of observations. Also, [, "name"] indexing doesn't work with matrices. Make sure you pass in a data.frame and not a matrix as in your example. Perhaps you want the by function instead
那是因为聚合不会将data.frames传递给它的FUN =参数。它传递了观察向量。此外,[,“name”]索引不适用于矩阵。确保传入data.frame而不是示例中的矩阵。也许你想要by功能
by(data.frame(var1 = 1:10, var2 = 101:110),
list(range=cut(1:10, breaks=c(2,4,8,10))),
FUN = function(x) { c(obs=length(x[, "var2"]), avg=mean(x[, "var2"]), sd=sd(x[, "var2"])) })
#1
3
Supply a dataframe and understand that aggregate passes only column vectors so using x[ , "colname"] is doomed because "x" is not a dataframe:
提供数据帧并理解聚合只传递列向量,因此使用x [,“colname”]注定要失败,因为“x”不是数据帧:
aggregate(data.frame(var1 = 1:10, var2 = 101:110),
by=list(range=cut(1:10, breaks=c(2,4,8,10))),
FUN = function(x)
{
c(obs=length(x), avg=mean(x), sd=sd(x))
})
#------------
range var1.obs var1.avg var1.sd var2.obs var2.avg var2.sd
1 (2,4] 2.0000000 3.5000000 0.7071068 2.0000000 103.5000000 0.7071068
2 (4,8] 4.0000000 6.5000000 1.2909944 4.0000000 106.5000000 1.2909944
3 (8,10] 2.0000000 9.5000000 0.7071068 2.0000000 109.5000000 0.7071068
#2
3
That's because aggregate doesn't pass data.frames to its FUN= argument. It passes the vector of observations. Also, [, "name"] indexing doesn't work with matrices. Make sure you pass in a data.frame and not a matrix as in your example. Perhaps you want the by function instead
那是因为聚合不会将data.frames传递给它的FUN =参数。它传递了观察向量。此外,[,“name”]索引不适用于矩阵。确保传入data.frame而不是示例中的矩阵。也许你想要by功能
by(data.frame(var1 = 1:10, var2 = 101:110),
list(range=cut(1:10, breaks=c(2,4,8,10))),
FUN = function(x) { c(obs=length(x[, "var2"]), avg=mean(x[, "var2"]), sd=sd(x[, "var2"])) })