[datatable-help] Idea/feature request

[Matthew Dowle]

Andreas, Steve,

Committed. Please test and confirm if it satisfies all needs ok?

o    A new symbol .BY is available to j, containing 1 row
     of the current 'by' variables, type list. 'by' variables
     may also be used by name and they are now length 1, too.
     This implements FR#1313.
     For example :
          DT[,sum(x)*.BY[[1]],by=y]
          DT[,sum(x)*.BY[[1]],by=eval(byexp)]
          DT[,sapply(.SD,sum)*y,by=y]
          DT[,sapply(.SD,sum)*.BY[[2]],by=list(y,z)]

Matthew



On Wed, 2011-05-11 at 10:24 +0200, Andreas Borg wrote:
> Hi Steve,
> 
> > Now that you've brought this back up, what do you think you would
> > prefer? For example, using my (admittedly contrived) original example:
> >
> > result <- some.big.data.table[, by=list(colA, colB), {
> >  ## Sometimes I want to know what the current values of
> >  ## colA and colB are in here to get some more info. Mabye
> >  ## we can have .BY:
> >
> >  xref <- more.data[J(.BY[1], .BY[2]), mult='all'] ## or something
> >  ## ...
> > }]
> >
> > Should it be `J(.BY[1], .BY[2])` or is something like `J(colA, colB)`
> > more natural, you think?
> >
> >   
> 'J(colA, colB)' is perfect if you know the column names in advance. This 
> is not true in my case. I created a minimal example for a possible 
> application for a '.BY' construct:
> 
>  > dt <- data.table(x=c(0,1,0,1), y=c(1,0,1,0))
>  > dt
>      x y
> [1,] 0 1
> [2,] 1 0
> [3,] 0 1
> [4,] 1 0
> 
>  From this table, I want the row sum for each group, i.e. "select x + y 
> from dt group by x, y" in SQL. This would be:
> 
>  > setkey(dt, x, y)
>  > dt[,sum(x[1], y[1]), by=list(x,y)]
>      x y V1
> [1,] 0 1  1
> [2,] 1 0  1
> 
> But what if dt can have an arbitrary number of (grouping) columns with 
> arbitrary names? If the grouping columns are given as
> 
> groupCols <- c("x", "y")
> 
> , the following is possible:
> 
>  > expr <- parse(text = sprintf("sum(%s)", paste(groupCols, "[1]", 
> sep="", collapse=", ")))
>  > dt[,eval(expr), by=groupCols]
>      x y V1
> [1,] 0 1  1
> [2,] 1 0  1
> 
> Now, this is certainly uglier than
> 
>  > dt[, sum(.BY), by = groupCols]
> 
> My actual application is that I apply decision tree models (rpart) to a 
> large number of binary patterns. In order to save computation time, I 
> classify each distinct pattern only once. So what I basically do is to 
> group by all attributes and apply the model once to each group.
> 
> Andreas
>