这是一个简单的dplyr解决方案.请注意，将后缀添加到新变量中比较容易，例如获取M1_M而不是MM1.但是，如果您想重命名它们，可以在之后设置colnames(请参见例如

Here is a simple dplyr solution. Note that it is easier to add a suffix to the new variables e.g. to get M1_M rather than MM1. However, you can set the colnames afterwards if you were keen to rename them (see e.g. here on how to do that).

我将结果显示为tibble，因此您可以看到列类型.请注意，一旦新列中同时包含UP和NA，它将从逻辑类型更改为字符类型.

I show the result as a tibble so you can see the column types. Note that once a new column has a both an UP and an NA in it, it will change from a logical type to a character type.

library(dplyr)

textdata <- "M1  M2  M3 UCL
1   2   3   1.5"

mydf <- read.table(text = textdata, header = T)

mydf %>% 
    mutate_if(is.integer, as.numeric) %>% 
    mutate_at(vars(starts_with("M")), funs(M = ifelse(. > UCL, "UP", NA))) %>% 
    tibble::as.tibble()

# A tibble: 1 x 7
     M1    M2    M3   UCL  M1_M  M2_M  M3_M
  <dbl> <dbl> <dbl> <dbl> <lgl> <chr> <chr>
1     1     2     3   1.5    NA    UP    UP