👀 Views: 79 💬 Answers: 1 📅 Created: 2025-06-16

r dplyr mutate R

Does anyone know how to I'm collaborating on a project where I'm facing an issue when trying to apply a custom function within `dplyr::mutate()`... I have a dataset with two columns: `value` and `threshold`, and I want to create a new column called `status` that indicates whether `value` exceeds `threshold`. However, when I run the code, I'm getting unexpected NA values in the `status` column. Here's the code snippet I'm using: ```r library(dplyr) # Sample data set.seed(123) data <- data.frame( value = c(5, 10, 15, 20, 25), threshold = c(10, 5, 20, 30, NA) ) # Custom function to check if value exceeds threshold check_status <- function(value, threshold) { if (is.na(threshold)) { return(NA) } else if (value > threshold) { return("Above") } else { return("Below") } } # Applying custom function within mutate result <- data %>% mutate(status = check_status(value, threshold)) print(result) ``` When I run this code, the output shows that the `status` column has NA for the last entry, which I expected since the `threshold` value is NA. However, I also see an unexpected NA for the first entry which has a valid threshold value of 10. The output looks like this: ``` value threshold status 1 5 10 Below 2 10 5 Above 3 15 20 Below 4 20 30 Below 5 25 NA <NA> ``` I checked the custom function, and it seems like it should work correctly for all entries. I even tried simplifying the function to return a constant value and it still resulted in NA for the first entry. I'm using R version 4.1.0 and `dplyr` version 1.0.7. Does anyone know why I'm encountering this issue? Any insights or solutions would be greatly appreciated! What's the correct way to implement this? The project is a service built with R. Hoping someone can shed some light on this.