[datatable-help] Follow-up on subsetting data.table with NAs

Mon Jun 10 16:55:28 CEST 2013

I prefer ~ and/or NJ() over -. The not-join operation is different from the
subsetting operation usually associated with -.

I don't know what characters are available for this sort of thing, but @x,
@(x,y) seems natural enough as syntax for a getter.

On Mon, Jun 10, 2013 at 9:35 AM, Matthew Dowle <mdowle at mdowle.plus.com>wrote:

>
> Hm, another good point.   We need ~ for formulae,  although I can't
> imagine a formula in i (only in j).  But in both i and j we might want to
> get(x).
>
> I thought about ^ i.e. X[^Y] in the spirit of regular expression syntax,
>  but ^ doesn't parse with a RHS only. Needs to be parsable as a prefix.
>
> - maybe then?  Consistent with - meaning in R.  I don't think I actually
> had a specific use in mind for - and +, to reserve them for,  but at the
> time it just seemed a shame to use up one of -/+ without defining the
> other.  If - does a not join, then, might + be more like merge() (i.e.
> returning the union of the rows in x and i by join).  I think I had
> something like that in mind, but hadn't thought it through.
>
> Some might say it should be a new argument e.g. notjoin=TRUE,  but my
> thinking there is readability,  since we often have many lines in i, j and
> by in that order, and if the "notjoin=TRUE" followed afterwards it would be
> far away from the i argument to which it applies.  If we incorporate
> merge() into X[Y] using X[+Y] then it might avoid adding yet more
> parameters, too.
>
>
>
> On 10.06.2013 15:02, Gabor Grothendieck wrote:
>
>> The problem with ~ is that it is using up a special character (of
>> which there are only a few) for a case that does not occur much.
>>
>> I can think of other things that ~ might be better used for.  For
>> example, perhaps ~ x could mean get(x).  One aspect of data.table that
>> tends to be difficult is when you don't know the variable name ahead
>> of time and this woiuld give a way to specify it concisely.
>>
>> On Mon, Jun 10, 2013 at 5:21 AM, Arunkumar Srinivasan
>> <aragorn168b at gmail.com> wrote:
>>
>>> Matthew,
>>>
>>> How about ~ instead of ! ?      I ruled out - previously to leave + and -
>>> available for future use.  NJ() may be possible too.
>>>
>>> Both "NJ()" and "~" are okay for me.
>>>
>>> That result makes perfect sense to me.   I don't think of !(x==.) being
>>> the
>>> same as  x!=.    ! is simply a prefix.    It's all the rows that aren't
>>> returned if the ! prefix wasn't there.
>>>
>>> I understand that `DT[!(x)]` does what `data.table` is designed to do
>>> currently. What I failed to mention was that if one were to consider
>>> implementing `!(x==.)` as the same as `x != .` then this behaviour has
>>> to be
>>> changed. Let's forget this point for a moment.
>>>
>>> That needs to be fixed.  But we're getting quite theoretical here and far
>>> away from common use cases.  Why would we ever have row numbers of the
>>> table, as a column of the table itself and want to select the rows by
>>> number
>>> not mentioned in that column?
>>>
>>> Probably I did not choose a good example. Suppose that I've a data.table
>>> and
>>> I want to get all rows where "x == 0". Let's say:
>>>
>>> set.seed(45)
>>> DT <- data.table( x = sample(c(0,5,10,15), 10, replace=TRUE), y =
>>> sample(15))
>>>
>>> DF <- as.data.frame(DT)
>>>
>>> To get all rows where x == 0, it could be done with DT[x == 0]. But it
>>> makes
>>> sense, at least in the context of data.frames, to do equivalently,
>>>
>>> DF[!(DF$x), ] (or) DF[DF$x == 0, ]
>>>
>>> All I want to say is, I expect `DT[!(x)]` should give the same result as
>>> `DT[x == 0]` (even though I fully understand it's not the intended
>>> behaviour
>>> of data.table), as it's more intuitive and less confusing.
>>>
>>> So, changing `!` to `~` or `NJ` is one half of the issue for me. The
>>> other
>>> is to replace the actual function of `!` in all contexts. I hope I came
>>> across with what I wanted to say, better this time.
>>>
>>> Best,
>>>
>>> Arun
>>>
>>>
>>> On Monday, June 10, 2013 at 10:52 AM, Matthew Dowle wrote:
>>>
>>>
>>>
>>> Hi,
>>>
>>> How about ~ instead of ! ?      I ruled out - previously to leave + and -
>>> available for future use.  NJ() may be possible too.
>>>
>>> Matthew
>>>
>>>
>>>
>>> On 10.06.2013 09:35, Arunkumar Srinivasan wrote:
>>>
>>> Hi Matthew,
>>> My view (from the last reply) more or less reflects mnel's comments here:
>>>
>>> http://stackoverflow.com/**questions/16239153/dtx-and-**
>>> dtx-treat-na-in-x-**inconsistently#**comment23317096_16240143<http://stackoverflow.com/questions/16239153/dtx-and-dtx-treat-na-in-x-inconsistently#comment23317096_16240143>
>>> Pasted here for convenience:
>>> data.table is mimicing subset in its handling of NA values in logical i
>>> arguments. -- the only issue is the ! prefix signifying a not-join, not
>>> the
>>> way one might expect. Perhaps the not join prefix could have been NJ not
>>> !
>>> to avoid this confusion -- this might be another discussion to have on
>>> the
>>> mailing list -- (I think it is a discussion worth having)
>>>
>>> Arun
>>>
>>> On Monday, June 10, 2013 at 10:28 AM, Arunkumar Srinivasan wrote:
>>>
>>> Hm, good point.  Is data.table consistent with SQL already, for both ==
>>> and
>>> !=, and so no change needed?
>>>
>>> Yes, I believe it's already consistent with SQL. However, the current
>>> interpretation of NA (documentation) being treated as FALSE is not
>>> needed /
>>> untrue, imho (Please see below).
>>>
>>>
>>> And it was correct for Frank to be mistaken.
>>>
>>> Yes, it seems like he was mistaken.
>>>
>>> Maybe just some more documentation and examples needed then.
>>>
>>> It'd be much more appropriate if the documentation reflects the role of
>>> subsetting in data.table mimicking "subset" function (in order to be in
>>> line
>>> with SQL) by dropping NA evaluated logicals. From a couple of posts
>>> before,
>>> where I pasted the code where NAs are replaced to FALSE were not
>>> necessary
>>> as `irows <- which(i)` makes clear that `which` is being used to get
>>> indices
>>> and then subset, this fits perfectly well with the interpretation of NA
>>> in
>>> data.table.
>>>
>>> Are you happy that DT[!(x==.)] and DT[x!=.] do treat NA inconsistently? :
>>>
>>>
>>> http://stackoverflow.com/**questions/16239153/dtx-and-**
>>> dtx-treat-na-in-x-**inconsistently<http://stackoverflow.com/questions/16239153/dtx-and-dtx-treat-na-in-x-inconsistently>
>>>
>>>  Ha, I like the idea behind the use of () in evaluating expressions. It's
>>> another nice layer towards simplicity in data.table. But I still think
>>> there
>>> should not be an inconsistency in equivalent logical operations to
>>> provide
>>> different results. If !(x== .) and x != . are indeed different, then I'd
>>> suppose replacing `!` with a more appropriate name as it's much easier to
>>> get confused otherwise.
>>> In essence, either !(x == .) must evaluate to (x != .) if the underlying
>>> meaning of these are the same, or the `!` in `!(x==.)` must be replaced
>>> to
>>> something that's more appropriate for what it's supposed to be.
>>> Personally,
>>> I prefer the former. It would greatly tighten the structure and
>>> consistency.
>>>
>>> "na.rm = TRUE/FALSE" sounds good to me.  I'd only considered nomatch
>>> before
>>> in the context of joins, not logical subsets.
>>>
>>> Yes, I find this option would give more control in evaluating expressions
>>> with ease in `i`, by providing both "subset" (default) and the typical
>>> data.frame subsetting (na.rm = FALSE).
>>> Best regards,
>>>
>>> Arun
>>>
>>>
>>>
>>>
>>>
>>>
>>>
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>>
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