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)]