Dear R community,
I find R fantastic and use R whenever I can for my data analytic
needs. Certain data sets, however, are so large that other tools
seem to be needed to pre-process data such that it can be brought
into R for further analysis.
Questions I have for the many expert contrib
package, for instance.
I am currently playing with parallelizing R computations via
Hadoop. I
haven't looked at PIG yet though.
Rory
-Original Message- From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Roland Rau
Sent: 21
August 2008 20:04 To: Avram Aelony Cc: r
Others may have mentioned this, but you might try loading your data
in a small database like mysql and then pulling smaller portions of
your data in via a package like RMySQL or RODBC.
One approach might be to split the data file into smaller pieces
outside of R, then read the smaller pie
Dear List,
I have a wrapper function that draws a graph that I'd like to use in a
vector-like manner. The for-loop version I currently use is below.
library(ggplot2)
data(economics)
h <- 600
w <- 800
#--
draw_metric_by_date <- functio
Dear List,
Hadley offered the following solution:
>library(plyr)
>l_ply(2:6, draw_metric_by_date, df = economics, smooth = TRUE, BASEPATH =
>basepath)
Many thanks,
Avram
On Wednesday, April 29, 2009, at 12:59PM, "Avram Aelony" wrote:
>
>Dear List,
>
>
Dear R list,
What is the best way to efficiently marry an R dataset with a very large
(Oracle) database table?
The goal is to only return Oracle table rows that match IDs present in the R
dataset.
I have an R data frame with 2000 user IDs analogous to: r =
data.frame(userid=round(runif(20
y the
>> matching rows out.
>>
>> -Aaron
>>
>> On Thu, Sep 11, 2008 at 2:33 PM, Avram Aelony <[EMAIL PROTECTED]> wrote:
>>>
>>> Dear R list,
>>>
>>> What is the best way to efficiently marry an R dataset with a very large
&
ble(connection, "r_user_ids")
>
>Of course, I don't know whether the ODBC driver implements these
>functions or not. (Is 'RODBC' built on DBI? Looks like Aaron and I
>have been assuming that.)
>
>Coey
>
> > -Aaron
> >
> > On Thu, S
.
Avram
On Thursday, September 11, 2008, at 02:19PM, "Coey Minear" <[EMAIL PROTECTED]>
wrote:
>Avram Aelony writes:
> >
> > I have not devoted time to setting up ROracle since binaries are
> > not available and it seems to require some effort to compile (se
Hello,
Although my summary descriptives are generated outside of R (dataset
is huge), I would like to produce a box-whisker plot using bxp or
perhaps a function from the ggplot2 library using the precomputed
summaries.
My dataset currently contains 10 rows (one row per week) with the
fo
or perhaps...
data1$NinYear <- with(data1, ave(ID, Year, FUN = length))
> unique(data1)
ID Year NinYear
1 209 1971 2
3 213 1951 2
5 213 1953 20
20 213 1954 11
31 213 1955 2
33 234 1953 20
38 234 1958 2
40 234 1965 3
43 249 1952 2
A
I experienced a similar problem generating PNGs on linux and found
that installing a missing font library corrected the situation.
Hope this helps,
Avram
On Dec 19, 2008, at 12:46 PM, Jeroen Ooms wrote:
I use a CentOS 5.2 VPS to generate graphs through an R web-
application. I
generate
Has anyone had success with producing legends to a qplot graph such that the
legend is placed on the bottom, under the abcissa rather than to the right hand
side ?
The following doesn't move the legend:
library(ggplot2)
qplot(mpg, wt, data=mtcars, colour=cyl, gpar(legend.position=
I usually have a function like this:
vplayout <- function(x, y) viewport(layout.pos.row=x, layout.pos.col=y)
draw4 <- function(pngname, a,b,c,d,w,h) {
png(pngname,width=w, height=h)
grid.newpage()
pushViewport(viewport(layout=grid.layout(2,2) ) )
print(a, vp=vplayout(1,1))
A few questions about maps...
(1) How can I find a listing of the internal data sets that map() from the maps
library contains?
For example, "usa", "county", "state", "nz" all work. Are there any others?
(2) Is there an easier, more generalized way to produce this
(http://www.ai.rug.nl/~hedder
On Tuesday, December 02, 2008, at 04:40PM, "hadley wickham" <[EMAIL PROTECTED]>
wrote:
>On Tue, Dec 2, 2008 at 6:21 PM, Avram Aelony <[EMAIL PROTECTED]> wrote:
>> A few questions about maps...
>>
>> (1) How can I find a listing of the internal dat
aha!, thanks for this.
Avram
On Dec 2, 2008, at 5:38 PM, Ray Brownrigg wrote:
On Wed, 03 Dec 2008, Ray Brownrigg wrote:
The easiest way would be:
map('world', regions="UK", xlim=c(-10, 5), ylim=c(48, 60))
But of course:
map('world', regions=c("UK", "Ireland"), xlim=c(-10, 5), ylim=c(48,
Hello,
I am running into memory boundaries and would like to try to make use of the
bigmemory (or any other memory enabling) library.
Can anyone help with suggestions as to how this might work?
> library(reshape)
> s <- melt( d[,1:62], id=c(1) )
Error: cannot allocate vector of size 16.0 Mb
>
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