Using one data.frame to update another

Question

Given 2 data frames that are identical in terms of column names/datatypes, where some columns uniquely identify the rows, is there an efficient function/method for one data.frame to "update" the other?

For example, in the following, original and replacement are identified by 'Name' and 'Id'. goal is the result of finding all rows from replacement in original (by the unique id's) and replacing with Value1 and Value2

original = data.frame( Name = c("joe","john") , Id = c( 1 , 2) , Value1 = c(1.2,NA), Value2 = c(NA,9.2) )
replacement = data.frame( Name = c("john") , Id = 2 , Value1 = 2.2 , value2 = 5.9)
goal = data.frame( Name = c("joe","john") , Id = c( 1 , 2) , Value1 = c(1.2,2.2), Value2 = c(NA,5.9) )

The solution should work for an original and replacement of arbitrary length (although replacement should never have more rows than original). In practice, I'm using 2 id columns.

Answer 1

I'd use data.table objects. This code seems to work on your example:

library(data.table)

# set keys
original.dt <- data.table(original, key=c("Name", "Id"))        
replacement.dt <- data.table(replacement, key=c("Name", "Id"))

goal2 <- original.dt
# subset and reassign
# goal2[replacement.dt[, list(Name, Id)]] <- replacement.dt
goal2[replacement.dt] <- replacement.dt  # cleaner and faster, see Matthew's comment

goal2 <- as.data.frame(goal2)

identical(goal, goal2) # FALSE, why? See Joris's comment
all.equal(goal, goal2) # TRUE