I have a grouped data_frame with a "tag" column taking on values "0" and "1". In each group, I need to find the first occurrence of "1" and change all the remaining occurrences to "0". Is there a way to achieve it in dplyr?
For example, let's take "iris" data and let's add the extra "tag" column:
data(iris)
set.seed(1)
iris$tag <- sample( c(0, 1), 150, replace = TRUE, prob = c(0.8, 0.2))
giris <- iris %>% group_by(Species)
In "giris", in the "setosa" group I need to keep only the first occurrence of "1" (i.e. in 4th row) and set the remaining ones to "0". This seems a bit like applying a mask or something...
Is there a way to do it? I have been experimenting with "which" and "duplicated" but I did not succeed. I have been thinking about filtering the "1"s only, keeping them, then joining with the remaining set, but this seems awkward, especially for a 12GB data set.