问题
There seems to be a minor difference between data.tabel's assignment by reference := in the standard to the functinal form.
Standard form coerces RHS to vector, the functional form does not. A detail, but not documented as I believe.
library(data.table)
dt <- data.table(a = c('a','b','c'))
v <- c('A','B','C')
l <- list(v)
all.equal(copy(dt)[, new := v], copy(dt)[, `:=` (new = v)])
# [1] TRUE
all.equal(copy(dt)[, new := l], copy(dt)[, `:=` (new = l)])
# [1] "Datasets have different column modes. First 3: new(character!=list)"
copy(dt)[, new := l][]
# a new
# 1: a A
# 2: b B
# 3: c C
copy(dt)[, `:=` (new = l)][]
# a new
# 1: a A,B,C
# 2: b A,B,C
# 3: c A,B,C
This is a major Edit of how I asked this question originally.
回答1:
This is very good question that touches design decision about := operator.
For simple calls using := as an operator, like col := val, we decided to wrap val into a list automatically. This decision was made to make it more convenient for users to assign single column.
When you are using function call form, ":="(col = val) we are not wrapping val into list anymore. It is extended form already. := behaves as an alias to list but updating in-place. You can always check what will be the updated column by changing := into list (or .) like .(col = val).
Not that even when using := as an operator, you still have to provide RHS as list of you are creating 2+ columns, c("col1","col2") := list(val1, val2).
来源：https://stackoverflow.com/questions/44067091/different-results-for-standard-form-and-functional-form-of-data-table-assigne-by