Summing data frames with different length - r

Question

I have two data sets (one for each country) that look like this:
dfGermany
Country Sales Year Code
Germany 2000 2000 221
Germany 1500 2001 150
Germany 2150 2002 270
dfJapan
Country Sales Year Code
Japan 500 2000 221
Japan 750 2001 221
Japan 800 2001 270
Japan 1000 2002 270
Code here is the "name" of the product. What I want to do is to take half the Japanese sell and add it to the df for Germany if the code and the year matches.
So for instance, half of the sales value for product 221 and 270 in dfJapan (250 € and 500 €) should be added to dfGermany for year 2000 and 2002. But nothing should happen to the values for 2001 since the code does not match with the year.
I tried with merge, but that function did not work since the data is of different size and I also want to match both year and value.

Answer 1

We can do a join on 'Year', 'Code' and then update the 'dfGermany' 'Sales' column
library(data.table)
setDT(dfGermany)[dfJapan, Sales := Sales + i.Sales/2, on = .(Year, Code)]
dfGermany
# Country Sales Year Code
#1: Germany 2250 2000 221
#2: Germany 1500 2001 150
#3: Germany 2650 2002 270
data
dfGermany <- structure(list(Country = c("Germany", "Germany", "Germany"),
Sales = c(2000, 1500, 2150), Year = 2000:2002, Code = c(221L,
150L, 270L)), row.names = c(NA, -3L), class = "data.frame")
dfJapan <- structure(list(Country = c("Japan", "Japan", "Japan", "Japan"
), Sales = c(500L, 750L, 800L, 1000L), Year = c(2000L, 2001L,
2001L, 2002L), Code = c(221L, 221L, 270L, 270L)),
class = "data.frame", row.names = c(NA, -4L))

Answer 2

Using dplyr and #akrun's provided data:
library(dplyr)
dfGermany %>%
left_join(dfJapan %>%
select(Year, Code, sales_japan = Sales),
by = c('Year', 'Code')) %>%
mutate(Sales = Sales + coalesce(sales_japan / 2, 0)) %>%
select(-sales_japan)
> dfGermany
Country Sales Year Code
1 Germany 2250 2000 221
2 Germany 1500 2001 150
3 Germany 2650 2002 270