complicated group_by +summarize

[help]

name place  first_time money_spent
Anna Florida TRUE          44
Anna Florida FALSE         22
Anna Florida FALSE         289
Anna Florida FALSE         0
Ryan Mexico  FALSE         0
Ryan Mexico  TRUE         122
Ryan Mexico  FALSE         0

hey all quick question. above is my data. for each group (name, place) I want to see how many times there is a non-zero, positive value in money_spent that doesn't have a first_time value as TRUE.

so when I do group_by and summarize, for group (Anne/Florida), it should be 2. Since she has a value in money_spent in two rows with first_time as FALSE that are non-zero and positive. For Ryan Mexico, it should be 0. Since he has money_spent as 0 in all rows that have first_time as FALSE.

thank you

[scottyd22]

If your dataset is df, you could do the following:

library(tidyverse)

df %>%
   group_by(name, place) %>%
   summarise(n = sum(first_time == FALSE & money_spent > 0)) %>%
   ungroup()

[help]

period! thank you!!<3