在 R 的 for 循环中的 if else 语句中使用 grepl()

Question

I am trying to use grepl() within an if else string within a for loop in order to do something I figure is pretty common in R: I have one column that has long names for plots, and I am trying to take information from that plot column and generate new columns based on that information. For this example, I will provide a version of my data to explain what I have tried:

for(i in seq_along(data)) {
  if(grepl("1987", data$id) == TRUE) {
    print("dnr87")
  } else if { (grepl("1994", data$id) == TRUE) {
else
print("no id") 
}

I receive the warning:

the condition has length > 1 and only the first element will be used

My questions are:

1. I understand that an if else statement designed this way only works on a single object, but since I nested it within a for loop, shouldn't it proceed to apply its process to each row?
2. Am I using grepl correctly? Shouldn't this effectively pick up on the features I am targeting?
3. How can I get this data to output into the corresponding rows into my empty column called "plot" below? This is the least of my concerns, because if I am able to get it to spit out the data, I can just merge the data into that column if needed.

Obviously, as seen in the data below, I would like to design the for loop to also go through and assign the same kind of data not only based on a grepl for year, but a grepl for ID (for example, grepl("E14) for the first data point), but I figure if you all can help me with the previous mentioned questions I should be able to incorporate that without huge issues.

Data table (name: data)

id  stand   plot
E141987 NA  NA
E141987 NA  NA
E141987 NA  NA
E141987 NA  NA
E121994 NA  NA
E121994 NA  NA
E121994 NA  NA
E121994 NA  NA
E121994 NA  NA
E121994 NA  NA
E121994 NA  NA
E121994 NA  NA
W52012  NA  NA
W52012  NA  NA
W52012  NA  NA
W52012  NA  NA
W52012  NA  NA
W52012  NA  NA

Answer 1

Since you're not providing reproducible data to illustrate the procedure, here's some mock data. If I understand you correctly you want to mutate codes based on patterns. If that's the case you can use nested ifelse statements :

Data:

df <- data.frame(
  id = c("a87", "b87", "abc95", "a95", "x123")
)

Now you define the new column with the mutated values:

df$new <- ifelse(grepl("87", df$id), "new1",
                 ifelse(grepl("95", df$id), "new2", "new3"))

An ifelse clause takes three arguments as input: (i) the condition, (ii) what to do if the condition holds true, (iii) what to do if it doesn't. The execution of (iii) can be delayed by inserting yet another ifelse clause testing for a second condition. This in turn can be delayed yet again by a third condition and so on.

The result:

df
     id  new
1   a87 new1
2   b87 new1
3 abc95 new2
4   a95 new2
5  x123 new3

These are not your data but I guess you get the gist: there's no need for a for loop and you can nest one ifelse in another.