Creating data.frame in in R by comparing values with list-CodePudding

I'm trying to transform a data.frame in R by comparing its observations with values of a list. This means if the list says: "'1' is correct." Then every other value should be wrong or N.A.

As an example I created a data.frame, which contains 3 different Variables for 3 observations:

dat <- data.frame("Q" = c("a", "b", "a"),
                  "P" = c(1, 2, 4),
                  "R" = c("d", NA, "d"))

For each variable I defined a correct answer and wrote these in a list:

results <- list("a", 2, "d")

So for Variable Q only a would be correct, for P only 2 and therefor d is the correct answer for R. As i want to create a dataset with Dummy-Variables, the result should look like:

      [,1]  [,2]  [,3] 
[1,] "Yes" "No"  "Yes"
[2,] "No"  "Yes" "No" 
[3,] "Yes"  NA   "Yes"

I tried to create a loop, but the result is not as expected:

mylist <- list()


for (j in 1:3) {
  vec <- character(3)
  for (i in 1:3) {
    ifelse(dat[i,j] == results[j], vec[j] <- "Yes",
           ifelse((is.na(dat[i,j]) == TRUE), vec[j] <- NA, vec[j] <- "No"))
  }
  mylist[[j]] <- vec
}

df <- do.call("rbind",mylist)

     [,1]  [,2] [,3] 
[1,] "Yes" ""   ""   
[2,] ""    "No" ""   
[3,] ""    ""   "Yes"

I am very thankful for all of your answers :)

CodePudding user response：

mapply(`==`, dat, results)

         Q     P    R
[1,]  TRUE FALSE TRUE
[2,] FALSE  TRUE   NA
[3,]  TRUE FALSE TRUE

Or, to get your expected output, use t:

t(mapply(`==`, dat, results))

   [,1]  [,2]  [,3]
Q  TRUE FALSE  TRUE
P FALSE  TRUE FALSE
R  TRUE    NA  TRUE

CodePudding user response：

out <- apply(dat,1,FUN = \(x) x==results)

out2 <- out
out2[out] <- "Yes"
out2[!out] <- "No"

gives

> out2
  [,1]  [,2]  [,3] 
Q "Yes" "No"  "Yes"
P "No"  "Yes" "No" 
R "Yes" NA    "Yes"

CodePudding user response：

Here is a dplyr solution:

library(dplyr)

dat %>% 
  mutate(across(everything(), ~case_when(. %in% results ~ "yes",
                                            !(. %in% results) ~ "no",
                                            TRUE ~ NA_character_)))

    Q   P   R
1 yes  no yes
2  no yes  no
3 yes  no yes