In thinking about this a bit more I can see the argument for leaving the default at nomatch=NA. Consider these examples of indexing:
> letters[27] [1] NA > BOD[7,] Time demand NA NA NA nomatch=NA seems more compatible with these examples than nomatch=0. (At the same time this does not mean we could not also change the argument name from nomatch= to all.y= and add the other merge arguments (all.x=, by.x=, by.y=, by=) as well since it remains the case that R's merge() seems closer than R's match() to this functionality regardless of the default.) On Fri, May 3, 2013 at 4:42 PM, Gabor Grothendieck <[email protected]> wrote: > One can view data.table's generalization of indexing as the > realization that all indexing can conceptually be viewed as merging > where indexing with numeric values corresponds to merging with the > data.table's row numbers and indexing with logical values, L, is > equivalent to merging with which(L) so there are really not two types: > indexing and merging but just one type: merging that covers them all. > > > On Fri, May 3, 2013 at 1:01 PM, Arunkumar Srinivasan > <[email protected]> wrote: >> I am wondering if performing X[Y] as a "merge" in correspondence with R's >> base "merge", if the basic idea of "i" becomes confusing. That is, when "i" >> is not a data.table in X[i] it indexes by rows. When `i` is a data.table, >> instead of the current definition which is in par with the subletting >> operation that use `i` (here data.table) as an index to subset X and then >> JOIN both X and Y, we say, here X and Y are data.tables and we perform a >> merge. I think this becomes confusing regarding the purpose of `i`. >> >> Remember that the main purpose of having the X[Y] is to have the flexibility >> of using `j` to to filter/subset only the desired columns. So, for example >> if you want to get 1 column of Y out of 100 columns when joining, you do: >> X[Y, list(cols_of_x, one_col_of_y)] and here, it doesn't go with the >> traditional definition of merge. >> >> As much as I like the idea of having consistent syntax, I also love the >> feature of X[Y, j]. So I'm confused as to how to deal with this. >> >> Arun >> >> On Friday, May 3, 2013 at 6:54 PM, Gabor Grothendieck wrote: >> >> I think that from the viewpoint of compatibility and convenience it >> would be best to implement all.x and all.y and not rely on swapping X >> and Y. SQLite did something like this (they implemented left join but >> not right join based on the idea that all you have to do is swap join >> arguments) but the problem with it is that it adds a layer of mental >> specification effort if the actual problem is better stated in the >> unsupported orientation. >> >> On Fri, May 3, 2013 at 12:49 PM, Eduard Antonyan >> <[email protected]> wrote: >> >> Arun, it only needs the addition of smth like X[Y, keep.all = TRUE], all of >> the other merge options already exist as either X[Y] or Y[X] with or without >> nomatch = 0/NA. >> >> >> On Fri, May 3, 2013 at 11:45 AM, Arunkumar Srinivasan >> <[email protected]> wrote: >> >> >> Gabor, >> >> Very true. I suppose your request is that the x[i] where `i` is a >> data.table should have the same set of options like R's base `merge` >> function, like, by.y=TRUE, by.x=TRUE or all=TRUE. I like the idea by itself. >> However, I am not able to think of a way to do this. I mean, I find the >> syntax X[Y, by.x=TRUE] weird / not making sense. That is, to me even though >> >> X[Y] is equal to Y[X, by.y=TRUE] (or) X[Y, by.x=TRUE] (ignoring the >> reordered columns) the latter 2 don't seem to make sense/is redundant (maybe >> it's because I am used to this syntax). >> >> Arun >> >> On Friday, May 3, 2013 at 5:57 PM, Gabor Grothendieck wrote: >> >> In my last post it should have read: >> >> That X[Y] is not the same as Y[X] is analogous to the fact that >> merge(X, Y, all.y=TRUE) is not the same as merge(Y, X, all.y=TRUE) >> >> On Fri, May 3, 2013 at 11:55 AM, Gabor Grothendieck >> <[email protected]> wrote: >> >> Assuming same-named keys, then these are all the same except possibly >> for row and column order: >> >> X[Y,,nomatch=0] >> Y[X,,nomatch=0] >> merge(X, Y) >> merge(Y, X) >> >> That X[Y] is not the same as Y[X] is analogous to the fact that >> merge(X, Y, all.x=TRUE) is not the same as merge(Y, X, all.x=TRUE) >> >> On Fri, May 3, 2013 at 11:46 AM, Arunkumar Srinivasan >> <[email protected]> wrote: >> >> Gabor, >> >> X[Y] and Y[X] are not necessarily the same operations (meaning, they don't >> *have* to give the same output). However, merge(X,Y) and merge(Y,X) *have* >> to provide the same output (except for the column order and names). In >> that >> sense, a join is a bit different from a merge, no? >> >> Arun >> >> On Friday, May 3, 2013 at 5:36 PM, Gabor Grothendieck wrote: >> >> Yes, except that is not really what happens since match() only matches >> one row whereas with mult="all", the default, all rows are matched >> which is not really matching in the sense of match(). The current >> naming confuses matching with joining and its really the latter that >> is being done. >> >> Regarding the existence of merge the advantage of [ is that it will >> automatically only take the columns needed so merge is not really >> equivalent to [ in all respects. Furthermore having to use different >> constructs for different types of merge seems awkward. >> >> >> On Fri, May 3, 2013 at 11:27 AM, Eduard Antonyan >> <[email protected]> wrote: >> >> Btw the way I think about the "nomatch" name is as follows - normally X[Y] >> tries to match rows of Y with rows of X, and then "nomatch" tells it what >> to >> do when there is *no match*. >> >> >> On Fri, May 3, 2013 at 10:23 AM, Eduard Antonyan >> <[email protected]> >> wrote: >> >> >> To clarify - that behavior is already implemented in merge (more >> specifically merge.data.table). I don't really have a view on having it in >> X[Y] as well - I don't like all.x and all.y as the names, since there are >> no >> params named 'x' and 'y' in [.data.table (as opposed to merge), but some >> param that would do a full outer join could certainly be added. >> >> >> On Fri, May 3, 2013 at 10:09 AM, Gabor Grothendieck >> <[email protected]> wrote: >> >> >> Yes, sorry. Its nomatch= which presumably derives from the parameter >> of the same name in the match() function. If the idea of the nomatch= >> name was to leverage off existing argument names in R then I would >> prefer all.y= to be consistent with merge() in place of nomatch= since >> we are really merging/joining rather than just matching. That would >> also allow extension to all types of join by adding all.an x= argument >> too. >> >> On Fri, May 3, 2013 at 10:59 AM, Eduard Antonyan >> <[email protected]> wrote: >> >> I would prefer nomatch=0 as a default though, simply because that's >> what I >> do most of the time :) >> >> >> On Fri, May 3, 2013 at 9:57 AM, Eduard Antonyan >> <[email protected]> >> wrote: >> >> >> A correction - the param is called "nomatch", not "match". >> >> This use case seems like smth a user shouldn't really do - in an ideal >> world you should have them both keyed by the same-name column. >> >> As is, my view on it is that data.table is correcting the user mistake >> of >> naming the column in Y - y, instead of x, and so the output makes >> sense and >> I don't see the need of complicating the behavior by adding more cases >> one >> has to go through to figure out what the output columns would be. >> Similar to >> asking for X[J(c("b", "c", "d"))] - you wouldn't want an anonymous >> column >> there, would you? >> >> >> >> On Fri, May 3, 2013 at 6:18 AM, Gabor Grothendieck >> <[email protected]> wrote: >> >> >> I am moving this discussion which started with mdowle to the list. >> >> Consider this example slightly modified from the data.table FAQ: >> >> X = data.table(x=c("a","a","b","b","b","c","c"), foo=1:7, key="x") >> Y = data.table(y=c("b","c","d"), bar=c(4,2,3)) >> out <- X[Y]; out >> >> x foo bar >> 1: b 3 4 >> 2: b 4 4 >> 3: b 5 4 >> 4: c 6 2 >> 5: c 7 2 >> 6: d NA 3 >> >> Note that the first column of the output is labelled x even though >> the >> data to produce it comes from y, e.g. "d" in out$x is not in X$x but >> does appear in Y$y so clearly the data is coming from y as opposed to >> x . In terms of SQL the above would be written: >> >> select Y.y as x, ... >> >> and the need to renamne the first column of out suggests that there >> may be a deeper problem here. >> >> Here are some ideas to address this (they would require changes to >> data.table): >> >> - the default of X[Y,, match=NA] would be changed to a default of >> X[Y,,match=0] so that it corresponds to the defaults in R's merge and >> in SQL joins. >> >> - the column name of the first column in the example above would be >> changed to y if match=0 but be left at x if match=NA. In the case >> that match=0 (the proposed new default) x and y are equal so the >> first >> column can be validly labelled as x but in the case that match=NA >> they >> are not so y would be used as the column name. >> >> - the name match= does seem a bit misleading since R's match only >> matches one item in the target whereas in data.table match matches >> many if mult="all" and that is the default. Perhaps some thought >> should be given to a name change here? >> >> The above would seem to correspond more closely to R's merge and SQL >> join defaults. Any use cases or other comments? >> >> -- >> Statistics & Software Consulting >> GKX Group, GKX Associates Inc. >> tel: 1-877-GKX-GROUP >> email: ggrothendieck at gmail.com >> _______________________________________________ >> datatable-help mailing list >> [email protected] >> >> >> >> https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/datatable-help >> >> >> >> >> -- >> Statistics & Software Consulting >> GKX Group, GKX Associates Inc. >> tel: 1-877-GKX-GROUP >> email: ggrothendieck at gmail.com >> >> >> >> >> -- >> Statistics & Software Consulting >> GKX Group, GKX Associates Inc. >> tel: 1-877-GKX-GROUP >> email: ggrothendieck at gmail.com >> _______________________________________________ >> datatable-help mailing list >> [email protected] >> >> https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/datatable-help >> >> >> >> >> -- >> Statistics & Software Consulting >> GKX Group, GKX Associates Inc. >> tel: 1-877-GKX-GROUP >> email: ggrothendieck at gmail.com >> >> >> >> >> -- >> Statistics & Software Consulting >> GKX Group, GKX Associates Inc. >> tel: 1-877-GKX-GROUP >> email: ggrothendieck at gmail.com >> >> >> >> >> -- >> Statistics & Software Consulting >> GKX Group, GKX Associates Inc. >> tel: 1-877-GKX-GROUP >> email: ggrothendieck at gmail.com >> >> > > > > -- > Statistics & Software Consulting > GKX Group, GKX Associates Inc. > tel: 1-877-GKX-GROUP > email: ggrothendieck at gmail.com -- Statistics & Software Consulting GKX Group, GKX Associates Inc. tel: 1-877-GKX-GROUP email: ggrothendieck at gmail.com _______________________________________________ datatable-help mailing list [email protected] https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/datatable-help
