r - Date difference per ID with dplyr without hours, minutes or seconds -

i'm trying similar done in post below. using dplyr. however, avoid conversion minutes months, highest precision of date variable in current database months..

calculating time difference id

   incident.id.. = c(rep("incfi0000029582",4), rep("incfi0000029587",4))    date = c("2014-09-11", "2014-10-11", "2014-11-11", "2014-12-11", "2015-01-11", "2015-02-11", "2015-03-11", "2015-04-11")    df = data.frame(incident.id..,date, stringsasfactors = false)  library(dplyr) library(lubridate) df %>%     group_by(incident.id..) %>%     mutate(diff = c(0, diff(ymd_hms(date))))  source: local data frame [8 x 3] groups: incident.id..   `enter code here`   incident.id..        date.diff 1 incfi0000029582 2014-09-25 08:39:45       0 2 incfi0000029582 2014-09-25 08:39:48       3 3 incfi0000029582 2014-09-25 08:40:44      56 4 incfi0000029582 2014-10-10 23:04:00 1347796 5 incfi0000029587 2014-09-25 08:33:32       0 6 incfi0000029587 2014-09-25 08:34:41      69 7 incfi0000029587 2014-09-25 08:35:24      43 8 incfi0000029587 2014-10-10 23:04:00 1348116 

i tried converting date variable as.date format , using dplyr functions below

library(dplyr) library(lubridate) df %>%   group_by(incident.id..) %>%   mutate(diff = c(0, diff(date))) 

but i'm getting result:

    incident.id..       date  diff             <chr>     <date> <dbl> 1 incfi0000029582 2014-09-11     0 2 incfi0000029582 2014-10-11    30 3 incfi0000029582 2014-11-11    31 4 incfi0000029582 2014-12-11    30 5 incfi0000029587 2015-01-11    31 6 incfi0000029587 2015-02-11    31 7 incfi0000029587 2015-03-11    28 8 incfi0000029587 2015-04-11    31 

i result shown below (date difference calculated using first encounter per id):

    incident.id..       date  diff             <chr>     <date> <dbl> 1 incfi0000029582 2014-09-11     0 2 incfi0000029582 2014-10-11    30 3 incfi0000029582 2014-11-11    61 4 incfi0000029582 2014-12-11    91 5 incfi0000029587 2015-01-11    0 6 incfi0000029587 2015-02-11    31 7 incfi0000029587 2015-03-11    59 8 incfi0000029587 2015-04-11    90 

any idea how done? thank help.

albit

solution minimum date per id in new column , subtract each date.

min_date<-df%>%group_by(incident.id..)%>%summarise(min_date=min(date))  df<-df%>%left_join(min_date,by="incident.id..")