r - How to merge two data.table by different column names?

Question

I have two data.table X and Y.

columns in X: area, id, value
columns in Y: ID, price, sales

Create the two data.tables:

X = data.table(area=c('US', 'UK', 'EU'),
               id=c('c001', 'c002', 'c003'),
               value=c(100, 200, 300)
              )

Y = data.table(ID=c('c001', 'c002', 'c003'),
               price=c(500, 200, 400),
               sales=c(20, 30, 15)
              )

And I set keys for X and Y:

setkey(X, id)
setkey(Y, ID)

Now I try to join X and Y by id in X and ID in Y:

merge(X, Y)
merge(X, Y, by=c('id', 'ID'))
merge(X, Y, by.x='id', by.y='ID')

All raised error saying that column names in the by argument invalid.

I referred to the manual of data.table and found the merge function not supporting by.x and by.y arguments.

How could I join two data.tables by different column names without changing the column names?

Append:
I managed to join the two tables by X[Y], but why merge function fails in data.table?

Answer 1

As of data.table version 1.9.6 (on CRAN on sep 2015) you can specify the by.x and by.y arguments in data.table::merge

merge(x=X, y=Y, by.x="id", by.y="ID")[]
#     id area value price sales
#1: c001   US   100   500    20
#2: c002   UK   200   200    30
#3: c003   EU   300   400    15

However, in data.table 1.9.6 you can also specfy the on argument in the X[Y] notation

X[Y] syntax can now join without having to set keys by using the new on argument. For example: DT1[DT2, on=c(x = "y")] would join column "y" of DT2 with "x" of DT1. DT1[DT2, on="y"] would join column "y" of both data.tables.

X[Y, on=c(id = "ID")]
#   area   id value price sales
#1:   US c001   100   500    20
#2:   UK c002   200   200    30
#3:   EU c003   300   400    15

this answer by the data.table author has more details