[datatable-help] Discrepancy between as.data.frame & as.data.table when handling nested lists

[Eduard Antonyan]

This seems like a pretty natural interpretation of list->data.table to me,
although it would be nice to maybe get a warning I think here:

    X = list(a = list(1,2), b = list(1,2,3))

    as.data.table(X)

especially since this simply refuses to do anything:

    data.table(a = c(1,2), b = c(1,2,3))


On Wed, Aug 7, 2013 at 10:30 PM, Ricardo Saporta <
saporta at scarletmail.rutgers.edu> 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 <FErickson at psu.edu> 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 <
>> saporta at scarletmail.rutgers.edu> 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)
>>>
>>>
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>>>
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>>>
>>
>>
>
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