data.table sum and subset

Single liner in data.table:

dt1[, lapply(.SD,sum), by=.(year,group)][, if (sum(amt) > 100) .SD, by=group]

#   group year amt
#1:     a 2001  60
#2:     a 2002  65

This might not be an idea solution, but I would do that in several steps as follows:

dt2=dt1[, sum(amt),by=list(year,group)]
dt3=dt1[, sum(amt)>100,by=list(group)]
dt_result=dt2[group %in% dt3[V1==TRUE]$group,]

You can do:

library(dplyr)
dt1 %>% 
  group_by(group, year) %>% 
  summarise(amt = sum(amt)) %>%
  filter(sum(amt) > 100)

Which gives:

#Source: local data table [2 x 3]
#Groups: group
#
#  year group amt
#1 2001     a  60
#2 2002     a  65

Here's a two-liner. Find the subset of groups you want first

big_groups <- dt1[,sum(amt),by=group][V1>100]$group
dt1[group%in%big_groups,sum(amt),by=list(year,group)]

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