问题描述
我同时具有数值和非<数值列的数据，例如：
I have data with both numeric and non-numeric columns like this:
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
如何仅选择数字列并使用 data.table ？
How can I select only numeric columns and calculate their mean using data.table?
我已经尝试过：
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>)
我也尝试了以下方法，但不起作用：
I have also tried the following, but it does not work:
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))"
按照@Arun的建议，我尝试了以下操作，但无法获得子集：
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所建议的那样，我尝试了以下操作，但对于非数字列却得到了 NULL 值。我想获取mydt的子集，以便甚至不列出其他列。
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
我缺少data.frame：
I am missing 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
确定。感谢David的评论，以下工作如下：
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 ，我进入了，我认为这很好地解释了如何使用它。
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
在做 mydt [，sapply（mydt，is.numeric ），= = FALSE] （注意： 现代方法是 mydt [，.SD，.SDcols = is.numeric] ）效率不高，因为它子集您的data.table带有这些列，并进行（深层）复制-不必要地使用了更多内存。
Doing mydt[, sapply(mydt, is.numeric), with = FALSE] (note: the "modern" way to do that is mydt[ , .SD, .SDcols = is.numeric])is not that efficient because it subsets your data.table with those columns and that makes a (deep) copy - more memory used unnecessarily.
并使用 colMeans 将data.table强制转换为 matrix ，这又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.
这篇关于使用data.table计算所有数字列的摘要统计信息（例如均值）的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！