Since you are dynamically building a variable name as a character value, it makes more sense to do assignment using standard data.frame indexing which allows for character values for column names. For example: multipetal <- function(df, n) { varname <- paste(“petal”, n , sep=”.”) df[[varname]] <- with(df, Petal.Width * n) df } The mutate function … Read more
If you want to take column sums you can iris %>% select_if(is.numeric) %>% mutate_all(funs(./sum(.))) If you want to take a total sum, you can just store it as another column iris %>% select_if(is.numeric) %>% mutate(totsum = sum(.)) %>% mutate_at(vars(-totsum), funs(./totsum)) I don’t think there is much merit to using dplyr for such non column or … Read more
The following will convert all non-zero numeric values to 1: df.richness %>% mutate_if(is.numeric, ~1 * (. != 0)) while df.richness %>% mutate_if(is.numeric, ~1 * (. > 0)) will do that with those greater than zero.