从data.table只获取R中的数字列 [英] get from data.table only numeric columns in R
问题描述
我有以下数据和代码。我想得到所有数字列的意思。当前代码给出警告。如何只选择数字列，然后找到它们的含义：
I have following data and code. I want to get mean of all numeric columns. Current code give warnings. How can I select only numeric columns and then find their means:
> mydt
vnum1 vint1 vfac1 vch1
1: -0.30159484 8 3 E
2: -0.09833430 8 1 D
3: -2.15963282 1 3 D
4: 0.03904374 5 2 B
5: 1.54928970 4 1 C
6: -0.73873654 5 1 A
7: -0.68594479 9 2 B
8: 1.35765612 1 2 E
9: 1.46958351 2 1 B
10: -0.89623979 2 4 E
>
> mydt[,lapply(.SD, mean),]
vnum1 vint1 vfac1 vch1
1: -0.046491 4.5 NA NA
Warning messages:
1: In mean.default(X[[3L]], ...) :
argument is not numeric or logical: returning NA
2: In mean.default(X[[4L]], ...) :
argument is not numeric or logical: returning NA
>
>
> dput(mydt)
structure(list(vnum1 = c(-0.301594844692861, -0.0983343040483769,
-2.15963282153076, 0.03904374068617, 1.54928969700272, -0.738736535236348,
-0.685944791146016, 1.35765612481877, 1.46958350568506, -0.896239790653183
), vint1 = c(8L, 8L, 1L, 5L, 4L, 5L, 9L, 1L, 2L, 2L), vfac1 = structure(c(3L,
1L, 3L, 2L, 1L, 1L, 2L, 2L, 1L, 4L), .Label = c("1", "2", "3",
"4"), class = "factor"), vch1 = structure(c(5L, 4L, 4L, 2L, 3L,
1L, 2L, 5L, 2L, 5L), .Label = c("A", "B", "C", "D", "E"), class = "factor")), .Names = c("vnum1",
"vint1", "vfac1", "vch1"), class = c("data.table", "data.frame"
), row.names = c(NA, -10L), .internal.selfref = <pointer: 0x991c070>)
我尝试下面但不工作：
> mydt[,lapply(.SD, is.numeric),]
vnum1 vint1 vfac1 vch1
1: TRUE TRUE FALSE FALSE
>
> mydt[,mydt[,lapply(.SD, is.numeric),]]
vnum1 vint1 vfac1 vch1
1: TRUE TRUE FALSE FALSE
>
> mydt[,mydt[,lapply(.SD, is.numeric),], with=F]
Error in Math.data.frame(j) :
non-numeric variable in data frame: vnum1vint1vfac1vch1
> mydt[,c(mydt[,lapply(.SD, is.numeric)),], with=F]
Error: unexpected ')' in "mydt[,c(mydt[,lapply(.SD, is.numeric))"
>
根据@Arun建议，我尝试了以下操作但无法获取子集：
As suggested by @Arun, I tried following but cannot get a subset:
> xx = mydt[,lapply(.SD, is.numeric),]
> xx
vnum1 vint1 vfac1 vch1
1: TRUE TRUE FALSE FALSE
> mydt[,lapply(.SD,mean),.SDcols=xx]
Error in `[.data.table`(mydt, , lapply(.SD, mean), .SDcols = xx) :
.SDcols should be column numbers or names
正如@David建议的，非数字列的值。我想获得mydt的一个子集，以便其他列甚至不列出。
As suggested by @David, I tried following but get NULL values for non-numeric columns. I want to get a subset of mydt so that other columns are not even listed.
> mydt[, lapply(.SD, function(x) if(is.numeric(x)) mean(x))]
vnum1 vint1 vfac1 vch1
1: -0.046491 4.5 NULL NULL
我正在使用data.frame：
I am mising data.frame:
> sapply(mydf, is.numeric)
vnum1 vint1 vfac1 vch1
TRUE TRUE FALSE FALSE
> mydf[sapply(mydf, is.numeric)]
vnum1 vint1
1 -0.30159484 8
2 -0.09833430 8
3 -2.15963282 1
4 0.03904374 5
5 1.54928970 4
6 -0.73873654 5
7 -0.68594479 9
8 1.35765612 1
9 1.46958351 2
10 -0.89623979 2
>
> sapply(mydf[sapply(mydf, is.numeric)], mean)
vnum1 vint1
-0.046491 4.500000
好的。感谢David的评论，以下作品：
OK. Thanks to David's comment, following works:
mydt[, sapply(mydt, is.numeric), with = FALSE][,sapply(.SD, mean),]
vnum1 vint1
-0.046491 4.500000
> mydt[, sapply(mydt, is.numeric), with = FALSE]
vnum1 vint1
1: -0.30159484 8
2: -0.09833430 8
3: -2.15963282 1
4: 0.03904374 5
...
推荐答案
通过在SO上搜索 .SDcols ，我登录了这个答案，我认为解释很好地使用它。
By searching on SO for .SDcols, I landed up on this answer, which I think explains quite nicely how to use it.
cols = sapply(mydt, is.numeric)
cols = names(cols)[cols]
mydt[, lapply(.SD, mean), .SDcols = cols]
# vnum1 vint1
# 1: -0.046491 4.5
c> mydt [，sapply（mydt，is.numeric），with = FALSE] 不是那么高效，因为它子集你的data.table与那些列， （深）复制 - 更多不必要的内存。
Doing mydt[, sapply(mydt, is.numeric), with = FALSE] is not that efficient because it subsets your data.table with those columns and that makes a (deep) copy - more memory used unnecessarily.
使用 colMeans 将data.table强制转换为 matrix ，这也不是那么高效的内存。
And using colMeans coerces the data.table into a matrix, which again is not so memory efficient.
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