Reputation:
My question is essentially the same as this question: data.table join then add columns to existing data.frame without re-copy.
Basically I have a template with keys and I want to assign columns from other data.tables to the template by the same keys.
> template
id1 id2
1: a 1
2: a 2
3: a 3
4: a 4
5: a 5
6: b 1
7: b 2
8: b 3
9: b 4
10: b 5
> x
id1 id2 value
1: a 2 0.01649728
2: a 3 -0.27918482
3: b 3 0.86933718
> y
id1 id2 value
1: a 4 -1.163439
2: b 4 2.267872
3: b 5 1.083258
> template[x, value := i.value]
> template[y, value := i.value]
> template
id1 id2 value
1: a 1 NA
2: a 2 0.01649728
3: a 3 -0.27918482
4: a 4 -1.16343917
5: a 5 NA
6: b 1 NA
7: b 2 NA
8: b 3 0.86933718
9: b 4 2.26787248
10: b 5 1.08325793
>
But if x
and y
have say 100 columns, then it is not possible to write out the value := i.value
syntax for all columns. Is there a way to do the same thing but for all the columns in x
and y
?
EDIT:
If I do y[x[template]]
, then it creates separate value
columns, which is not intended:
> y[x[template]]
id1 id2 value value.1
1: a 1 NA NA
2: a 2 NA 0.01649728
3: a 3 NA -0.27918482
4: a 4 -1.163439 NA
5: a 5 NA NA
6: b 1 NA NA
7: b 2 NA NA
8: b 3 NA 0.86933718
9: b 4 2.267872 NA
10: b 5 1.083258 NA
>
Upvotes: 4
Views: 1430
Reputation: 118779
Just create a function that takes names as arguments and constructs the expression for you. And then eval
it each time by passing the names of each data.table
you require. Here's an illustration:
get_expr <- function(x) {
# 'x' is the names vector
expr = paste0("i.", x)
expr = lapply(expr, as.name)
setattr(expr, 'names', x)
as.call(c(quote(`:=`), expr))
}
> get_expr('value') ## generates the required expression
# `:=`(value = i.value)
template[x, eval(get_expr("value"))]
template[y, eval(get_expr("value"))]
# id1 id2 value
# 1: a 1 NA
# 2: a 2 0.01649728
# 3: a 3 -0.27918482
# 4: a 4 -1.16343900
# 5: a 5 NA
# 6: b 1 NA
# 7: b 2 NA
# 8: b 3 0.86933718
# 9: b 4 2.26787200
# 10: b 5 1.08325800
Upvotes: 5