This is great!! Sqldf is exactly the kind of thing I was looking for,
other stuff.
I suppose you can speed up both functions 1 and 5 using aggregate and
tapply only once, as was suggested earlier. But it comes at the
expense of readability.
Nikhil
On 9 Dec 2009, at 7:59AM, Titus von de
On Wed, Dec 9, 2009 at 7:59 AM, Titus von der Malsburg
wrote:
> On Wed, Dec 9, 2009 at 12:11 AM, Gabor Grothendieck
> wrote:
>> Here are a couple of solutions. The first uses by and the second sqldf:
>
> Brilliant! Now I have a whole collection of solutions. I did a simple
> performance compar
On Wed, Dec 9, 2009 at 12:11 AM, Gabor Grothendieck
wrote:
> Here are a couple of solutions. The first uses by and the second sqldf:
Brilliant! Now I have a whole collection of solutions. I did a simple
performance comparison with a data frame that has 7929 lines.
The results were as followin
Here are a couple of solutions. The first uses by and the second sqldf:
> Lines <- " rt dur tid mood roi x
+ 55 5523 200 4 subj 9 5
+ 56 5523 52 4 subj 7 31
+ 57 5523 209 4 subj 4 9
+ 58 5523 188 4 subj 4 7
+ 70 4016 264 5 indic 9 51
+ 71 4016 195 5 indic 4 14"
>
I've sent last message only to Titus. Sorry :)
Below my proposition:
Instead of aggregate, try summaryBy from doBy package. It's much
faster. And this package made my life easier :)
try:
summaryBy(dur+x~index, data=d, FUN=c(sum, mean)),
but index should be in data.frame as I remember.
I haven't
On Tue, Dec 8, 2009 at 5:19 PM, Nikhil Kaza wrote:
> I suppose that is true, but the example data seem to suggest that it is
> sorted by rt.
I was not very clear on that. Sorry.
> d$count <- 1
> a <- with(d, aggregate(subset(d, select=c("dur", "x", "count"),
> list(rt=rt,tid=tid,mood=mood,roi=
On Tue, Dec 8, 2009 at 4:50 PM, Gray Calhoun wrote:
> I think there might be a problem with this approach if roi, tid, rt,
> and mood are the same for nonconsecutive rows.
True, but I can use the index of my reshape solution. Aggregate was
the crucial ingredient. Thanks both!
For the record, th
I think there might be a problem with this approach if roi, tid, rt,
and mood are the same for nonconsecutive rows.
--Gray
On Tue, Dec 8, 2009 at 9:29 AM, Nikhil Kaza wrote:
> How about creating an index using multiple columns.
>
> a <- with(d, aggregate(dur, list(rt=rt,tid=tid,mood=mood,roi=roi
How about creating an index using multiple columns.
a <- with(d, aggregate(dur, list(rt=rt,tid=tid,mood=mood,roi=roi),
sum))
b <- with(d, aggregate(x, list(rt=rt,tid=tid,mood=mood,roi=roi),
mean))
c <- merge(a, b, by=c("rt","tid","mood", "roi"))
I suppose one could save some time by not r
Hi, I have a data frame and want to merge adjacent rows if some condition is
met. There's an obvious solution using a loop but it is prohibitively slow
because my data frame is large. Is there an efficient canonical solution for
that?
> head(d)
rt dur tid mood roi x
55 5523 200 4 subj
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