I want to write a
case_when code in a
dplyr pipeline. However, I am trying to add multiple cases within it.
For example: If a have the following data frame
I want to summarize the output so that case when the first 2 observations per each id are needs and case when the observation “none” is not put in consideration then put
yes in a new column. If there’s no need or want for a given id then
The output should be the following:
actions %>% group_by (id) %>% arrange(id) %>% summarise(output = case_when(first(purchases) == "need" & nth(purchases,2) =="need"~ "yes", "no"
I know the code is a bit messy, as I don’t know who to add up the second condition of neglecting
none observations when the cases would result in a
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