Duplicated rows: select rows based on criteria and store duplicated values

Question

I am working on a raw dataset that looks something like this:

df <- data.frame(\"ID\" = c(\"Alpha\", \"Alpha\", \"Alpha\", \"Alpha\", 
                                


        

Answer 1

Here is one option with dplyr. After grouping by 'ID', 'Year', create a logical column ('ind') that checks the max of 'Val2', using that create two columns corresponding to 'Val' with 'del' as prefix for those values that are eliminated, as well as the 'treatment' not present, filter the rows based on 'ind' and ungroup

library(dplyr)
df %>% 
   group_by(ID, Year) %>% 
   mutate(ind = Val2 == max(Val2) & !is.na(Val2)) %>% 
   mutate_at(vars(matches('Val')), 
        list(del = ~ if(any(!ind)) .[!ind] else NA_real_)) %>% 
   mutate(del_treat = if(any(!ind)) treatment[!ind] else NA_character_) %>% 
   filter(ind) %>%
   ungroup %>%
   select(-ind)