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我正在尝试使用rowSds()计算每行标准差，以便我可以选择具有高 sds 的行来绘制图表。

我的数据框被称为xx是这样的：

head(xx,1)
     Job     variable 2012-02-23 2012-02-24 2012-02-25 2012-02-27 2012-02-28 2012-02-29 2012-03-01 2012-03-02 2012-03-03 2012-03-05 2012-03-06 2012-03-07 2012-03-08 2012-03-09 2012-03-10 2012-03-12 2012-03-13 2012-03-14
1 A Duration        152        424         NA        499        320        117        211        363         NA        605         76        309        204        185         NA         25        733        500
  2012-03-15 2012-03-16 2012-03-17 2012-03-19 2012-03-20 2012-03-21 2012-03-22 2012-03-23 2012-03-24 2012-03-26 2012-03-27 2012-03-28 2012-03-29 2012-03-30 2012-03-31 2012-04-02 2012-04-03 2012-04-04 2012-04-05 2012-04-06
1        521        601         NA        229        758        421        334        659         NA        419        423        444        289        594         NA        327        533        183        211        235
  2012-04-07 2012-04-09 2012-04-10 2012-04-11 2012-04-12 2012-04-13 2012-04-14 2012-04-16 2012-04-17 2012-04-18 2012-04-19 2012-04-20 2012-04-21 2012-04-23 2012-04-24 2012-04-25 2012-04-26 2012-04-27 2012-04-28 2012-04-30
1         NA        225        419        236        218        188         NA        205        547        153        196        200         NA        259        257        208        302        244         NA        806
  2012-05-01 2012-05-02 2012-05-03 2012-05-04 2012-05-05 2012-05-07 2012-05-08 2012-05-09 2012-05-10 2012-05-11 2012-05-12 2012-05-14 2012-05-15 2012-05-16 2012-05-17 2012-05-18 2012-05-19 2012-05-21 2012-05-22 2012-05-23
1        402        492       1078        440         NA        382        576       1105        511        368         NA        360        381       1152        718        353         NA        408        413        935
  2012-05-24 2012-05-25 2012-05-26 2012-05-28 2012-05-29 2012-05-30 2012-05-31 2012-06-01 2012-06-02 2012-06-04 2012-06-05 2012-06-06 2012-06-07 2012-06-08 2012-06-09 2012-06-11 2012-06-12 2012-06-13 2012-06-14 2012-06-15
1        306        277         NA        253        367        977        557        432         NA        328        521        467        972       1556         NA        386       1394        401        857        857
  2012-06-16 2012-06-18 2012-06-19 2012-06-20 2012-06-21 2012-06-22 2012-06-23 2012-06-25 2012-06-26 2012-06-27 2012-06-28 2012-06-29 2012-06-30 2012-07-02 2012-07-03 2012-07-04 2012-07-05 2012-07-06 2012-07-07 2012-07-09
1         NA       1056        324        329        327        325         NA        341        268        231        245        301         NA        283        365        297        310        260         NA        254
  2012-07-10 2012-07-11 2012-07-12 2012-07-13 2012-07-14 2012-07-16 2012-07-17 2012-07-18 2012-07-19 2012-07-20 2012-07-21 2012-07-23 2012-07-24 2012-07-25 2012-07-26 2012-07-27 2012-07-28 2012-07-30 2012-07-31 2012-08-01
1        283        395        273        273         NA        278        243        210        356        267         NA        442        483        271        327        271         NA        716        598        577
  2012-08-02 2012-08-03 2012-08-06 2012-08-07 2012-08-08 2012-08-09 2012-08-10 2012-08-13 2012-08-14 2012-08-15 2012-08-16 2012-08-17 2012-08-20 2012-08-21 2012-08-22 2012-08-23 2012-08-24 2012-08-27 2012-08-28 2012-08-29
1        345        403        318        522        333        259        404        244        240        288        245         22        738        530        390        648        294        403        381        724
  2012-08-30 2012-08-31 2012-09-03 2012-09-04 2012-09-05 2012-09-06 2012-09-07 2012-09-10 2012-09-11 2012-09-12 2012-09-13 2012-09-14 2012-09-17 2012-09-18 2012-09-19 2012-09-20 2012-09-21 2012-09-24 2012-09-25 2012-09-26
1        740        575        558        785        883        501        901        500        285        174        562       1047        603        990        289        173        253        512        236        278
  2012-09-27 2012-09-28 2012-10-01 2012-10-02 2012-10-03 2012-10-04 2012-10-05 2012-10-08 2012-10-09 2012-10-10 2012-10-11 1        173        277        217        291        197        308        124        387        369        250        242

我正在尝试计算每一行的标准偏差并分配给 sd 列名：

xx$sd<-rowSds(xx)

我收到此错误：

Error in apply(na.omit(as.matrix(x), ...), 1, FUN, ...) : 
  error in evaluating the argument 'X' in selecting a method for function 'apply': Error in na.omit(as.matrix(x), ...) : 
  error in evaluating the argument 'object' in selecting a method for function 'na.omit': Error in `colnames<-`(`*tmp*`, value = c("2012-02-23", "2012-02-24", "2012-02-25",  : 
  length of 'dimnames' [2] not equal to array extent

NA计算 SD 时如何省略任何想法？我的语法正确吗？

4

2 回答 2

32

您可以使用apply和transform功能

set.seed(007)
X <- data.frame(matrix(sample(c(10:20, NA), 100, replace=TRUE), ncol=10))
transform(X, SD=apply(X,1, sd, na.rm = TRUE))
   X1 X2 X3 X4 X5 X6 X7 X8 X9 X10       SD
1  NA 12 17 18 19 16 12 13 20  14 3.041381
2  14 12 13 13 14 18 16 17 20  10 3.020302
3  11 19 NA 12 19 19 19 20 12  20 3.865805
4  10 11 20 12 15 17 18 17 18  12 3.496029
5  12 15 NA 14 20 18 16 11 14  18 2.958040
6  19 11 10 20 13 14 17 16 10  16 3.596294
7  14 16 17 15 10 11 15 15 11  16 2.449490
8  NA 10 15 19 19 12 15 15 19  14 3.201562
9  11 NA NA 20 20 14 14 17 14  19 3.356763
10 15 13 14 15 NA 13 15 NA 15  12 1.195229

从?apply您可以看到...哪些允许使用 FUN 的可选参数，在这种情况下，您可以使用na.rm=TRUE省略NA值。

rowSds从 matrixStats 包中使用也需要设置na.rm=TRUE为省略NA

library(matrixStats)
transform(X, SD=rowSds(X, na.rm=TRUE)) # same result as before.
于 2012-10-12T15:04:02.497 回答
1

也有效，基于这个答案

set.seed(007)
X <- data.frame(matrix(sample(c(10:20, NA), 100, replace=TRUE), ncol=10))

vars_to_sum = grep("X", names(X), value=T)
X %>% 
  group_by(row_number()) %>%
  do(data.frame(., 
                SD = sd(unlist(.[vars_to_sum]), na.rm=T)))

...它附加了几个行号列，因此可能更好地显式添加行 ID 以进行分组。

X %>% 
  mutate(ID = row_number()) %>%
  group_by(ID) %>%
  do(data.frame(., SD = sd(unlist(.[vars_to_sum]), na.rm=T)))

此语法还具有能够指定要使用的列的功能。

于 2020-04-02T23:27:42.120 回答