date - Flagging data within groups in R dataframe -

i have following table in r dataframe

i write logic generates "keep" column. each person flag accounts has transaction newer 4 days, since first access. first line new account person flag it. second line dates 2 days apart keep too. third line 11 days since first saw account not flag it. same logic goes next person. flag accounts less 4 days old.

i have rebuilt data frame, try solution:

library(lubridate) library(dplyr)  df <- data.frame(person = c(rep("abc",3), rep("eee", 5)),            date = c("4/1/2016", "4/3/2016", "4/12/2016", "5/3/2016", "5/4/2016","5/4/2016","5/6/2016", "5/10/2016"),            account = c("123","123","123","222","222","333","222","333"), stringsasfactors = f)  df$date2 <- mdy(df$date) 

the best solution, suggested @thelatemail:

df %>%  group_by(person) %>%  mutate(keep=as.numeric(date2 - first(date2) <= 4)) %>%  select(-date2) 

result:

 person      date account keep 1    abc  4/1/2016     123    1 2    abc  4/3/2016     123    1 3    abc 4/12/2016     123    0 4    eee  5/3/2016     222    1 5    eee  5/4/2016     222    1 6    eee  5/4/2016     333    1 7    eee  5/6/2016     222    1 8    eee 5/10/2016     333    0 

my more convoluted original solution (useful if account creation date not in first line each person):

df %>%  group_by(person) %>%  slice(which.min(date2)) %>% select(person, date2) %>% rename(account_create = date2) %>% merge(df, ., = "person") %>% mutate(keep = as.numeric(date2 - account_create <= 4)) %>% select(-c(date2, account_create))