Changing Binary Variables to Yes/No

R: Converting multiple binary columns into one factor variable whose factors are binary columns

I am guessing that you want to revert a "one-hot encoding" of a variable. Here is a quick way to do it.

apply(df ,1,\(x) names(which(x == "yes"))) |>
  purrr::map_chr(~ifelse(length(.x) == 0, NA_character_, .x))

#+  [1] "v1" "v1" "v3" "v1" "v1" "v2" "v1" "v2" "v3" NA  

A tidyverse approach would be:

df |>
  mutate(ID = row_number()) |>
  pivot_longer(cols = c(v1,v2,v3), names_to = "var") |>
  filter(value == "yes")

##>      ID var   value
##>   <int> <chr> <chr>
##> 1     1 v1    yes  
##> 2     2 v1    yes  
##> 3     3 v3    yes  
##> 4     4 v1    yes  
##> 5     5 v1    yes  
##> 6     6 v2    yes  
##> 7     7 v1    yes  
##> 8     8 v2    yes  
##> 9     9 v3    yes  

r program changing yes/no variable to 1/0 - variable 'medal' is not a factor

Apart from the obvious typo...

How can I change the yes/no to 0/1?

You need

sport$medal <- factor(sport$medal, levels = c("yes", "no"))

The default behaviour will give you 0 for "no" and 1 for "yes", as "n" comes ahead of "y" in alphabetical order.

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