On 18.11.2012 20:03, Steve Lianoglou wrote:
Hi,
On Sun, Nov 18, 2012 at 11:19 AM, Philip de Witt Hamer
<[email protected]> wrote:
Dear all,
data.table is great! thanks for this life(time)saving package.
Now, I run into a difficult nut to crack using ':='.
I'd like to do a calculation using column information conditional on
another
column
first some jumbo data:
library(data.table)
DT <- data.table(
1:50,
rep(1:5,each=10),
runif(50,0,1)
)
setnames(DT, 1:3, c("id","grp","p"))
id's are unique
grp's speaks for itself
think of p's as e.g. p-values
next, if I want to obtain the nr of p values at least as extreme as
the p of
each row from the whole set, this seems to work well:
DT[,c1 := sum(DT[,p] <= p), by=id]
but then, I would like to get the nr of p values at least as extreme
as the
p of each row for the subset with identical grp, I am having a hard
time,
because these attempts fail:
DT[,c2 := sum(DT[grp,p] <= p),by=id]
DT[,c3 := sum(DT[DT[,grp]==grp,p] <= p), by=id]
You will want to group by "grp".
This gets you pretty close -- it fails the "ties" criterion:
DT[, cg := rank(p) - 1, by=grp]
If you *really* want to keep the ties criterion, perhaps here's a way
to do so by avoiding a for loop:
DT[, cgo := rowSums(outer(p, p, '-') > 0), by=grp]
The problem is that if your groups are very large, the `outer` call
might chew lots of RAM, since you'll be creating a p x p matrix (per
group).
Does that get you where you need to be?
-steve
Grouping by grp feels right to me, too. How about :
setkey(DT,grp,p)
and then using the ordered p within each group :
DT[,c1:=seq_len(.N),by=grp]
DT[,c1:=max(c1),by='grp,p'] # to deal with ties
NB: data.table grouping of numerics is machine tolerance aware. So
this ties treatment is more like sum(DT[,p] <= p+tol) which may or
may not be what you need. tol = .Machine$double.eps ^ 0.5.
Or, staying with the self join approach, one trick for the scoping
issue you hit is :
DT[,c3:={i=list(grp);sum(DT[i,p]<=p)},by=id]
Where the DT[i,...] part relies on the fact that single name i is
evaluated
in calling scope.
Or another way in one step is :
DT[,c3:=sum(DT[eval(.(grp)),p]<=p),by=id]
which uses the feature that eval() is already like what ..() will do in
future.
But grouping by grp should be much faster and cleaner, if possible.
Matthew
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