Avoiding FOR LOOPs, how can I incrementally-index from a list?-CodePudding

I have a dataset similar to "mydf" and have opted to go through the following process in order to achieve the desired outcome data.frame "desired_outcome". This is a simplistic example with the real dataset including roughly 30 variable "Letters", hence my interest in streamlining the below code example.

library(dplyr)
mydf <- data.frame("Location" = factor(c("A10", "A10", "A11", "A11a", "A12", "B10", "B11", "B12")))
A_locs <- factor(c("A10", "A11", "A11a", "A12"))
B_locs <- factor(c("B10", "B11", "B12"))
mylst <- list("A's" = A_locs, "B's" = B_locs)

mydf$Letter <- NA #initialize new field within my data.frame
mydf$Letter[mydf$Location %in% mylst[[1]]] <- names(mylst)[1]
mydf$Letter[mydf$Location %in% mylst[[2]]] <- names(mylst)[2]

mydf
desired_outcome <- data.frame("Location" = factor(c("A10", "A10", "A11", "A11a", "A12", "B10", "B11", "B12")), 
                              "Letter" = factor(c("A's", "A's", "A's", "A's", "A's", "B's", "B's", "B's")))

I've had the idea of employing a FOR LOOP, although I would strongly prefer to find a more clever way to do this. The loop below does NOT produce the desired result, but is generally what I envisioned the loop itself looking like:

for (i in 1:length(names(mylst))){
  if(mydf$Location[i] %in% mylst[[i]]) {
    mydf$Letter <- names(mylst)[i]}
  return(mydf)
}

I've looked into employing functions such as lapply or sapply, but I am unfamiliar with these. Are there any clever methods I may use here to:

1.) clean up the code I've written and

2.) avoid long blocks of manual iteration without a FOR loop?

CodePudding user response：

If you are open to a tidyverse approach, you could try

library(tidyverse)

mydf %>% 
  mutate(Letter = deframe(map_dfr(mylst, tibble, .id = "name")[2:1])[Location])

This returns

  Location Letter
1      A10    A's
2      A10    A's
3      A11    A's
4     A11a    A's
5      A12    A's
6      B10    B's
7      B11    B's
8      B12    B's