advanced patterns when using `dplyr::mutate` with `case_when` for character columns in R 4.3
I'm experimenting with After trying multiple solutions online, I still can't figure this out... I've hit a wall trying to After trying multiple solutions online, I still can't figure this out... I've searched everywhere and can't find a clear answer. This might be a silly question, but I'm working with an scenario when trying to use `dplyr::mutate` along with `case_when` to create a new character column based on conditions applied to another character column. My dataset contains a column `status` with values like 'Active', 'Inactive', and 'Pending', and I want to create a new column `status_label` that assigns labels based on the value of `status`. However, the new column `status_label` is returning `NA` for some rows unexpectedly. Here's the code I used: ```r library(dplyr) my_data <- data.frame( id = 1:5, status = c('Active', 'Inactive', 'Pending', 'Active', 'Pending') ) my_data <- my_data %>% mutate(status_label = case_when( status == 'Active' ~ 'Currently Active', status == 'Inactive' ~ 'No Activity', status == 'Pending' ~ 'Awaiting Action', TRUE ~ NA_character_ )) ``` After running the code, I expected the `status_label` column to have values 'Currently Active', 'No Activity', and 'Awaiting Action' corresponding to the `status`, but instead, I see that the last row has `NA`. Could this be an scenario with how `case_when` handles character comparisons? I've already checked the exact string values in the `status` column and they match the conditions in `case_when`, but still, it's returning `NA`. Is there a best practice or alternative that I should consider for this type of operation? Any insights would be greatly appreciated! This is part of a larger API I'm building. For context: I'm using R on macOS. How would you solve this? My development environment is macOS. I'm coming from a different tech stack and learning R. How would you solve this?