如何解决使用mutate和gsub将所有值替换为特定列中的NA
在数据框中，我想将某些列中的所有值替换为NA。
Test2
ID Sex Location Obs1 Obs4 Obs5
1 291978 FEMALE 2 16.5 4836 0.563636364
2 292429 FEMALE 2 20.2 5428 0.584158416
3 292466 FEMALE 2 19.2 48 0.005208333
4 293656 FEMALE 2 15.8 2904 0.417721519
5 291993 FEMALE 2 18.1 6194 0.900552486
6 293263 FEMALE 2 17.9 616 0.078212291
7 290200 FEMALE 2 16.7 792 0.107784431
8 292511 FEMALE 2 18.3 4992 0.568306011
9 291510 FEMALE 2 18.6 350 0.037634409
10 293711 FEMALE 2 18.2 264 0.032967033
11 295234 FEMALE 2 16.5 216 0.036363636
12 293839 FEMALE 2 15.0 4114 0.806666667
13 291057 FEMALE 2 16.7 56 0.005988024
14 295094 FEMALE 2 16.5 3154 0.503030303
15 295562 FEMALE 2 14.7 966 0.142857143
16 292381 FEMALE 2 17.4 1980 0.258620690
17 289765 FEMALE 2 17.8 3492 0.544943820
18 293871 FEMALE 2 18.2 3760 0.516483516
19 291076 FEMALE 2 16.8 88 0.011904762
20 293851 FEMALE 2 16.1 2242 0.366459627
首先，我想指定应将哪些列的值替换为NA。只能是一列，也可以是多列。这就是为什么我更喜欢将其放入向量。
> Obs <- c('Obs1')
然后，我尝试使用以下方法将“ Obs1”列中的所有值替换为NA：
> deselect <- Test2 %>% mutate(across(paste(Obs),gsub(".*",NA,paste(Obs))))
但是，它给了我这个错误：
Error: Problem with `mutate()` input `..1`.
x Problem with `across()` input `.fns`.
i Input `.fns` must be NULL,a function,a formula,or a list of functions/formulas.
i Input `..1` is `across(paste(Obs),paste(Obs)))`.
Run `rlang::last_error()` to see where the error occurred.
有人知道如何在mutate内，mutate内使用gsub吗？还是应该使用其他方法？
非常感谢！
解决方法
或使用<!DOCTYPE html>
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mutate_at这就是您使用mutate和across的方式。
cols_na <- c("wt","hp")
mtcars %>%
mutate(across(one_of(cols_na),~ NA))
我建议使用一种base R方法，在Obs中定义要替换的列：
#Data
df <- structure(list(ID = c(291978L,292429L,292466L,293656L,291993L,293263L,290200L,292511L,291510L,293711L,295234L,293839L,291057L,295094L,295562L,292381L,289765L,293871L,291076L,293851L),Sex = c("FEMALE","FEMALE","FEMALE"),Location = c(2L,2L,2L),Obs1 = c(16.5,20.2,19.2,15.8,18.1,17.9,16.7,18.3,18.6,18.2,16.5,15,14.7,17.4,17.8,16.8,16.1),Obs4 = c(4836L,5428L,48L,2904L,6194L,616L,792L,4992L,350L,264L,216L,4114L,56L,3154L,966L,1980L,3492L,3760L,88L,2242L),Obs5 = c(0.563636364,0.584158416,0.005208333,0.417721519,0.900552486,0.078212291,0.107784431,0.568306011,0.037634409,0.032967033,0.036363636,0.806666667,0.005988024,0.503030303,0.142857143,0.25862069,0.54494382,0.516483516,0.011904762,0.366459627)),class = "data.frame",row.names = c("1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17","18","19","20"))
接下来的代码：
#Define cols
Obs <- c('Obs1')
#Assign
index <- which(names(df) %in% Obs)
df[,index] <- gsub(".*",NA,df[,index])
输出：
ID Sex Location Obs1 Obs4 Obs5
1 291978 FEMALE 2 <NA> 4836 0.563636364
2 292429 FEMALE 2 <NA> 5428 0.584158416
3 292466 FEMALE 2 <NA> 48 0.005208333
4 293656 FEMALE 2 <NA> 2904 0.417721519
5 291993 FEMALE 2 <NA> 6194 0.900552486
6 293263 FEMALE 2 <NA> 616 0.078212291
7 290200 FEMALE 2 <NA> 792 0.107784431
8 292511 FEMALE 2 <NA> 4992 0.568306011
9 291510 FEMALE 2 <NA> 350 0.037634409
10 293711 FEMALE 2 <NA> 264 0.032967033
11 295234 FEMALE 2 <NA> 216 0.036363636
12 293839 FEMALE 2 <NA> 4114 0.806666667
13 291057 FEMALE 2 <NA> 56 0.005988024
14 295094 FEMALE 2 <NA> 3154 0.503030303
15 295562 FEMALE 2 <NA> 966 0.142857143
16 292381 FEMALE 2 <NA> 1980 0.258620690
17 289765 FEMALE 2 <NA> 3492 0.544943820
18 293871 FEMALE 2 <NA> 3760 0.516483516
19 291076 FEMALE 2 <NA> 88 0.011904762
20 293851 FEMALE 2 <NA> 2242 0.366459627
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