您不必转换为数字，D[D >= 30]工作正常。>=也适用于字符向量，排序取决于您的语言环境。查看?Comparison了解更多详情。

D[D >= "30"]
#[1] "31" "32" "33" "34" "35" "36" "41" "42" "43" "44" "45" "46" "51" "52" "53" "54" "55" "56" "61" "62" "63" "64" "65" "66"

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对于排序，这将起作用（但可能只有当您有2位数的数字时）：

str_rev <- stringi::stri_reverse
str_rev(sort(str_rev(D[D >= "30"])))
# [1] "31" "41" "51" "61" "32" "42" "52" "62" "33" "43" "53" "63" "34" "44" "54" "64" "35"
#[18] "45" "55" "65" "36" "46" "56" "66"

型
str_sub：

library(stringr)        
D[order(str_sub(D, -1, -1))]

型

不知道我是否遵循你的逻辑，但这个解决方案怎么样？

D[str_detect(D,"^[12]\\d|0$")]

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正则表达式代码基本上是以1/2开头，后跟数字或0的任何代码。它需要stringr软件包9（tidyverse的一部分）。你可以使用baseR，但要习惯tidyverse，它更好（base R将是grepl(pattern,string)）否则我会def去D[D<30]，但这可能是作弊

请检查下面的代码

D2 <- enframe(D) %>% arrange(value) %>% filter(value>30) %>% 
mutate(value2=str_extract(value,'\\d$')) %>% 
  arrange(value2) %>% pull(value)

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创建于2023-07-14带有reprex v2.0.2

[1] "31" "41" "51" "61" "32" "42" "52" "62" "33" "43" "53" "63" "34"
[14] "44" "54" "64" "35" "45" "55" "65" "36" "46" "56" "66"

型

1.)可以通过比较操作!=来完成，该操作不进行数字转换（对于数字字符串<= 2位）。
2.)是一种排序操作，其内部可能依赖于数字或ASCII码表字母排序的转换。

D_new <- D[sapply(strsplit(D, ""), \(x) 
  ifelse(length(x) > 1 & x[1] != "1" & x[1] != "2", T, F))]

D_new[order(sapply(strsplit(D_new, ""), \(x) x[2]))]
 [1] "31" "41" "51" "61" "32" "42" "52" "62" "33" "43" "53" "63" "34" "44" "54"
[16] "64" "35" "45" "55" "65" "36" "46" "56" "66"

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另一种提取第二个数字的方法是将D除以10并使用余数。下面是它的样子：

library(tidyverse)

D <- D[D >= 30]

data.frame(D) |>
  mutate(second_digit = as.numeric(D) %% 10) |>
  arrange(second_digit) |>
  filter(D > 30) |>
  pull(D)
#>  [1] "31" "41" "51" "61" "32" "42" "52" "62" "33" "43" "53" "63" "34" "44" "54"
#> [16] "64" "35" "45" "55" "65" "36" "46" "56" "66"

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regex的另一个选择。任何数字3-9后面跟着另一个数字0-9。

D[grepl("^[3-9][0-9]", D)]
#>  [1] "31" "32" "33" "34" "35" "36" "41" "42" "43" "44" "45" "46" "51" "52" "53"
#> [16] "54" "55" "56" "61" "62" "63" "64" "65" "66"

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