通过连接分配 data.table 行和列的子集

Question

I'm trying to do something similar but different enough from what's described here: Update subset of data.table based on join

Specifically, I'd like to assign to matching key values ( person_id is a key in both tables) column values from table control. CI is the column index. The statement below says 'with=F' was not used . when I delete those parts, it also doesn't work as expected. Any suggestions?

To rephrase: I'd like to set the subset of flatData that corresponds to control FROM control.

flatData[J(eval(control$person_id)), ci, with=F] = control[, ci, with=F]

To give a reproducible example using classic R:

x = data.frame(a = 1:3, b = 1:3, key = c('a', 'b', 'c'))
y = data.frame(a = c(2, 5), b = c(11, 2), key = c('a', 'b'))

colidx = match(c('a', 'b'), colnames(y))

x[x$key %in% y$key, colidx] = y[, colidx]

As an aside, someone please explain how to easily assign SETS of columns without using indices! Indices and data.table are a marriage made in hell.

Answer 1

You can use the := operator along with the join simultaneously as follows:

First prepare data:

require(data.table) ## >= 1.9.0
setDT(x)            ## converts DF to DT by reference
setDT(y)
setkey(x, key)      ## set key column
setkey(y, key)

Now the one-liner:

x[y, c("a", "b") := list(i.a, i.b)]

:= modifies by reference (in-place). The rows to modify are provided by the indices computed from the join in i .

ia and ib are the column names data.table internally generates for easy access to i 's columns when both x and i have identical column names, when performing a join of the form x[i] .

HTH

PS: In your example y 's columns a and b are of type numeric and x 's are of type integer and therefore you'll get a warning when run on your data, that the types dint match and therefore a coercion had to take place.