Hadley,
That's fine; please do. I'm happy to explain it offline where the
documentation or comments in the
code aren't sufficient. It's GPL code so you can take it and improve it, or
depend on it.
Whatever works for you. As long as (of course) you don't stand on it's
shoulders and then
restric
> From: had...@rice.edu
> Date: Mon, 7 Feb 2011 11:00:59 -0600
> To: mdo...@mdowle.plus.com
> CC: r-h...@stat.math.ethz.ch
> Subject: Re: [R] aggregate function - na.action
>
> > Does FAQ 1.8 answer that ok ?
> >
> Does FAQ 1.8 answer that ok ?
> "Ok, I'm starting to see what data.table is about, but why didn't you
> enhance data.frame in R? Why does it have to be a new package?"
> http://datatable.r-forge.r-project.org/datatable-faq.pdf
Kind of. I think there are two sets of features data.table provi
Hi Hadley,
Does FAQ 1.8 answer that ok ?
"Ok, I'm starting to see what data.table is about, but why didn't you
enhance data.frame in R? Why does it have to be a new package?"
http://datatable.r-forge.r-project.org/datatable-faq.pdf
Matthew
"Hadley Wickham" wrote in message
news:AANLkT
On Mon, Feb 7, 2011 at 5:54 AM, Matthew Dowle wrote:
> Looking at the timings by each stage may help :
>
>> system.time(dt <- data.table(dat))
> user system elapsed
> 1.20 0.28 1.48
>> system.time(setkey(dt, x1, x2, x3, x4, x5, x6, x7, x8)) # sort by the
>> 8 columns (one-off)
>
Looking at the timings by each stage may help :
> system.time(dt <- data.table(dat))
user system elapsed
1.200.281.48
> system.time(setkey(dt, x1, x2, x3, x4, x5, x6, x7, x8)) # sort by the
> 8 columns (one-off)
user system elapsed
4.720.945.67
> system.time(
On Feb 6, 2011, at 7:41 PM, Hadley Wickham wrote:
There's definitely something amiss with aggregate() here since
similar
functions from other packages can reproduce your 'control' sum. I
expect
ddply() will have some timing issues because of all the subgrouping
in your
data frame, but data
> There's definitely something amiss with aggregate() here since similar
> functions from other packages can reproduce your 'control' sum. I expect
> ddply() will have some timing issues because of all the subgrouping in your
> data frame, but data.table did very well and the summaryBy() function i
Hi:
There's definitely something amiss with aggregate() here since similar
functions from other packages can reproduce your 'control' sum. I expect
ddply() will have some timing issues because of all the subgrouping in your
data frame, but data.table did very well and the summaryBy() function in t
Try 'data.table' package. It took 3 seconds to aggregate the 500K
levels: Is this what you were after?
> # note the characters are converted to factors that 'data.table' likes
> dat=data.frame(
+x1=sample(c(NA,'m','f'), 2e6, replace=TRUE),
+x2=sample(c(NA, 1:10), 2e6, replace=TRU
By the way, thanks for sending that formula, it's quite thoughtful of you to
send an answer with an actual working line of code!
When I experimented with ddply earlier last week I couldn't figure out the
syntax for a single line aggregation, so it's good to have this example. I
will likely use it
Try to use formula notation and use na.action=na.pass
It is all described in the help(aggregate)
У Няд, 06/02/2011 у 14:54 -0600, Gene Leynes піша:
> On Fri, Feb 4, 2011 at 6:54 PM, Ista Zahn wrote:
>
> > >
> > > However, I don't think you've told us what you're actually trying to
> > > accompl
On Fri, Feb 4, 2011 at 6:54 PM, Ista Zahn wrote:
> >
> > However, I don't think you've told us what you're actually trying to
> > accomplish...
> >
>
I'm trying to aggregate the y value of a big data set which has several x's
and a y.
I'm using an abstracted example for many reasons. Partially,
Ista,
Thank you again.
I had figured that out... and was crafting another message when you replied.
The NAs do come though on the variable that is being aggregated,
However, they do not come through on the categorical variable(s).
The aggregate function must be converting the data frame variabl
Just to be clear:
This works:
> set.seed(100)
> dat=data.frame(
+ x1=sample(c(NA,'m','f'), 100, replace=TRUE),
+ x2=sample(c(NA, 1:10), 100, replace=TRUE),
+ x3=sample(c(NA,letters[1:5]), 100, replace=TRUE),
+ x4=sample(c(NA,T,F), 100, replace=TRUE),
+ y=sam
oops. For clarity, that should have been
sum(ddply(dat, .(x1,x2,x3,x4), function(x){data.frame(y.sum=sum(x$y,
na.rm=TRUE))})$y.sum)
-Ista
On Fri, Feb 4, 2011 at 7:52 PM, Ista Zahn wrote:
> Hi again,
>
> On Fri, Feb 4, 2011 at 7:18 PM, Gene Leynes wrote:
>> Ista,
>>
>> Thank you again.
>>
>> I
Hi again,
On Fri, Feb 4, 2011 at 7:18 PM, Gene Leynes wrote:
> Ista,
>
> Thank you again.
>
> I had figured that out... and was crafting another message when you replied.
>
> The NAs do come though on the variable that is being aggregated,
> However, they do not come through on the categorical va
Hi,
On Fri, Feb 4, 2011 at 6:33 PM, Gene Leynes wrote:
> Thank you both for the thoughtful (and funny) replies.
>
> I agree with both of you that sum is the one picking up aggregate. Although
> I didn't mention it, I did realize that in the first place.
> Also, thank you Phil for pointing out th
Thank you both for the thoughtful (and funny) replies.
I agree with both of you that sum is the one picking up aggregate. Although
I didn't mention it, I did realize that in the first place.
Also, thank you Phil for pointing out that aggregate only accepts a formula
value in more recent versions!
Sorry, I didn't see Phil's reply, which is better than mine anyway.
-Ista
On Fri, Feb 4, 2011 at 5:16 PM, Ista Zahn wrote:
> Hi,
>
> Please see ?na.action
>
> (just kidding!)
>
> So it seems to me the problem is that you are passing na.rm to the sum
> function. So there is no missing data for th
Hi,
Please see ?na.action
(just kidding!)
So it seems to me the problem is that you are passing na.rm to the sum
function. So there is no missing data for the na.action argument to
operate on!
Compare
sum(aggregate(y~x1+x2+x3+x4, data=dat, sum, na.action=na.fail)$y)
sum(aggregate(y~x1+x2+x3+x4
Gene -
Let me try to address your concerns one at a time:
Since the formula interface to aggregate was introduced
pretty recently (I think R-2.11.1, but I might be wrong)
so when you try to use it in an R-2.10.1 it won't work.
Now let's take a close look at the help page for aggregate.
The
Can someone please tell me what is up with na.action in aggregate?
My (somewhat) reproducible example:
(I say somewhat because some lines wouldn't run in a separate session, more
below)
set.seed(100)
dat=data.frame(
x1=sample(c(NA,'m','f'), 100, replace=TRUE),
x2=sample(c(NA, 1:10
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