Type Age   count1  count2
  A   35    1        1
  A   35    3        1
  A   45    2        3
  B   45    2        1
  B   45    4        5

Type  Age  count1  count2
  A   35    4        2
  A   45    2        3
  B   45    6        6

typedup = duplicated(df$Type)
bothdup = duplicated(df[(typedup == TRUE),]$Age)

tapply(c(df$count1, df$count2), c(df$Age, df$Type), sum)

library(dplyr)
df1 %>%
     group_by(Type, Age) %>%
     summarise_each(funs(sum))
#    Type Age count1 count2
#1    A  35      4      2
#2    A  45      2      3
#3    B  45      6      6

aggregate(.~Type+Age, df1, FUN=sum)
 #    Type Age count1 count2
 #1    A  35      4      2
 #2    A  45      2      3
 #3    B  45      6      6

library(data.table)
setDT(df1)[, lapply(.SD, sum), .(Type, Age)]
#   Type Age count1 count2
#1:    A  35      4      2
#2:    A  45      2      3
#3:    B  45      6      6

sqldf("select
Type,Age,
sum(count1) as sum_count1,
sum(count2) as sum_count2
from
 df
group by
Type,Age
")