Agreed, intentional.
> L = list(1,2,3)
> as.data.table(L)
V1 V2 V3 # 3 columns, not one list column
1: 1 2 3
> L = list(1,2,3,list("a",4L,3:10)) # the one nested list here
creates one list column
> as.data.table(L)
V1 V2 V3 V4
1: 1 2 3 a
2: 1 2 3 4
3: 1 2 3 3,4,5,6,7,8,
Rick - are you asking for use cases of list columns full stop or use
cases of converting nested lists to data.table containing list columns ?
On 08/08/13 04:30, Ricardo Saporta wrote:
Hey Frank,
Thanks for pointing out that SO link, I had missed it.
All,
I'm curious as to which used cases this functionality would be used in
(used for?)
thanks,
Rick
On Wed, Aug 7, 2013 at 8:14 PM, Frank Erickson <[email protected]
<mailto:[email protected]>> wrote:
Hi Rick,
I guess it's intentional: Matthew saw this SO question (since he
edited one of the answers):
http://stackoverflow.com/questions/9547518/creating-a-data-frame-where-a-column-is-a-list
Some musings: Of course, to reproduce as.data.frame-like behavior,
you can un-nest the list, so both functions treat it the same way.
Z <- unlist(Y,recursive=FALSE)
identical(as.data.table(Z),as.data.table(as.data.frame(Z))) # TRUE
# or, equivalently (?)
identical(do.call(data.table,Z),data.table(do.call(data.frame,Z)))
# TRUE
On the other hand, going back the other direction (getting
data.table-like behavior when data.frame's is the default) is more
awkward, as seen in that SO question (where they mention
protecting each sublist with the I() function). Besides, I'm with
@flodel, who asked the SO question, in expecting data.table's
behavior: one top-level item in the list mapping to one column in
the result...
--Frank
On Wed, Aug 7, 2013 at 4:56 PM, Ricardo Saporta
<[email protected]
<mailto:[email protected]>> wrote:
Hi all,
Note the following discrepancy in structure between
as.data.frame & as.data.table when called on a nested list.
as.data.frame converts the sublist into individual columns
whereas as.data.table stacks them into a single column and
creates additional rows.
Is this intentional?
-Rick
as.data.frame(X)
# start type end data.editDist data.second
# 1 start_node is_similar end_node 1 HelloWorld
as.data.table(X)
# start type end data
# 1: start_node is_similar end_node 1
# 2: start_node is_similar end_node HelloWorld
### Copy+Paste'able Below ###
# Example 1:
X <- structure(list(start = "start_node", type =
"is_similar", end = "end_node",
data = structure(list(editDist = 1, second =
"HelloWorld"), .Names = c("editDist",
"second"))), .Names = c("start", "type", "end", "data"))
as.data.frame(X)
as.data.table(X)
as.data.table(as.data.frame(X))
# Example 2, with more elements:
Y <- structure(list(start = c("start_node", "start_node"),
type = c("is_similar", "is_similar"), end = c("end_node",
"end_node"), data = structure(list(editDist = c(1, 1), second
= c("HelloWorld", "HelloWorld")), .Names = c("editDist",
"second"))), .Names = c("start", "type", "end", "data"))
as.data.frame(Y)
as.data.table(Y)
_______________________________________________
datatable-help mailing list
[email protected]
<mailto:[email protected]>
https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/datatable-help
_______________________________________________
datatable-help mailing list
[email protected]
https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/datatable-help
_______________________________________________
datatable-help mailing list
[email protected]
https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/datatable-help
