r - 删除R中多个变量中的字符串

Question

这是我的数据的 MWE，我想从包含“Med”的所有列中删除字符串“NaN”

df= data.frame(id= rep(1:5, each=1),
               Med1 = c("GN", "GN", "Ca", "Ca", "DM"),
               Med2 = c("DM", "NaN", "Mob", "NaN", "NaN"),
               Med3 = c("NaN","NaN","DM", "NaN","NaN"))

我尝试了以下方法：

dfx = df%>%
  mutate(across(contains("Med", ignore.case = TRUE), str_remove(.,"NaN")))

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 `(function (.cols = everything(), .fns = NULL, ..., .names = NULL) ...`.
Run `rlang::last_error()` to see where the error occurred.
In addition: Warning message:
Problem with `mutate()` input `..1`.
i argument is not an atomic vector; coercing
i Input `..1` is `(function (.cols = everything(), .fns = NULL, ..., .names = NULL) ...`. 

dfx = df%>%
  mutate(across(contains("Med", ignore.case = TRUE), str_remove("NaN")))

Error: Problem with `mutate()` input `..1`.
x argument "pattern" is missing, with no default
i Input `..1` is `(function (.cols = everything(), .fns = NULL, ..., .names = NULL) ...`.

我也有从单个列中删除字符串的问题，所以我想我可能会误解str_remove

dfy=df%>%
 str_remove(string = Med1, pattern = "NaN")
Error in str_remove(., string = Med1, pattern = "NaN") : 
  unused argument (.)

Answer 1

预先：在您的代码中添加一个波浪号：

dfx = df%>%                                        # ,--- add this tilde
  mutate(across(contains("Med", ignore.case = TRUE), ~ str_remove(.,"NaN")))

---

说明：across将函数作为其第二个参数。这可以用几种方式表达：

1. 原始函数，例如across(everything(), mean). 您可以在之后添加任意命名/未命名参数，尽管它们与数据本身是分开的。

   mtcars %>%
     mutate(across(everything(), mean))
   mtcars %>%
     mutate(across(everything(), mean, na.rm = TRUE))
   

   （这不假设 base-R 函数：您可以在其他地方创建自己的函数并在此处传递它。）

2. 匿名函数，允许更灵活的调用。也许：

   mtcars %>%
     mutate(across(everything(), function(z) mean(x)))
   mtcars %>%
     mutate(across(everything(), function(z) mean(x, na.rm = TRUE)))
   

3. rlang-style 波浪号函数。在这些中，a.被数据向量替换（对于每一列是mutated）：

   mtcars %>%
     mutate(across(everything(), ~ mean(.)))
   mtcars %>%
     mutate(across(everything(), ~ mean(., na.rm = TRUE)))
   

---

当然，您不需要stringr执行此任务。

df
#   id Med1 Med2 Med3
# 1  1   GN   DM  NaN
# 2  2   GN  NaN  NaN
# 3  3   Ca  Mob   DM
# 4  4   Ca  NaN  NaN
# 5  5   DM  NaN  NaN
df[df == "NaN"] <- ""
df
#   id Med1 Med2 Med3
# 1  1   GN   DM     
# 2  2   GN          
# 3  3   Ca  Mob   DM
# 4  4   Ca          
# 5  5   DM