I have a data frame (df) with 7 rows and 4 columns (named c1, c2, c3, c4):
c1 c2 c3 c4
Yes No Yes No
Yes Yes No No
No Yes No No
Yes No No
You could try something like:
colnames(df) <- c("c1", "c2", "c3", "c4")
test <- (apply(df,1,function(x) which(x=="Yes")))
df$cols <- lapply(test,names)
This was along the lines of what you were initially trying I think.
To tidy the output you could:
df$cols <- gsub("c(", "", df$cols, fixed = TRUE)
df$cols <- gsub(")", "", df$cols, fixed = TRUE)
This removes the c().
We can loop (apply) through the rows (MARGIN=1) of the logical matrix (df=='Yes'), convert to 'numeric' index (which), get the names and paste it together with a wrapper toString which is paste(., collapse=', '). We may also need a if/else logical condition to check if there are any 'Yes' values in a row. If not, it should return NA.
df$Expected_Result <- apply(df=='Yes', 1, function(x) {
if(any(x)) {
toString(names(which(x)))
}
else NA
})
Or another option would to get the row/column index with which by specifying the arr.ind=TRUE. Grouped by the row of 'indx' (indx[,1]), we paste the column names of 'df' ('val'). If there are some rows missing i.e. without any 'Yes' element, then use ifelse to create NA for the missing row.
indx <- which(df=='Yes', arr.ind=TRUE)
val <- tapply(names(df)[indx[,2]], indx[,1], FUN=toString)
df$Expected_Result <- ifelse(seq_len(nrow(df)) %in% names(val), val, NA)
df <- structure(list(c1 = c("Yes", "Yes", "No", "Yes", "Yes", "Yes",
"No"), c2 = c("No", "Yes", "Yes", "No", "No", "No", "No"), c3 = c("Yes",
"No", "No", "No", "Yes", "No", "Yes"), c4 = c("No", "No", "No",
"No", "No", "No", "No")), .Names = c("c1", "c2", "c3", "c4"),
class = "data.frame", row.names = c(NA, -7L))
An option using data.table
library(data.table)
setDT(df)[, rownum:=1:.N,]
df$Expected_result <- melt(df, "rownum")[,
toString(variable[value=="Yes"]), rownum]$V1