Terrific! This is great to know.
I first tried saving and restoring the entire set from par3d but this
produced some changes (eg bg) and also one must call par3d with
no.readonly=TRUE. Clearly this is the way to go if one has changed a variety
of rgl properties. But if one has only used the mouse
After interacting with a 3d plot (eg plot3d, persp3d), is there a way to
capture the final settings of view angles, etc, so that the final plot could
be easily reproduced? The plot functions themselves just return a vector of
'ids'.
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An expression like "v >= 52", where v is a vector, will produce a vector
resulting from comparing each entry -- that is why you see the message.
What you want to do is logical subscripting. For example
names <- character( nrow( curveData ) )
names[ curvedata$Date.difference <= 29 ] = "< 1 mon
Sharpie wrote:
>
> You could try Sage:
>
> http://www.sagemath.org
>
Yes, I've tried Sage (briefly) and it is very interesting. But what I'm
looking for here is a client-server system that allows multiple users to
access the results of R without exposing the details.
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Based on a private response, it seems that rpad is no longer being maintained
and in fact no longer works with the latest R release. I noticed that the
web site listed in the FAQ no longer works, the code is being hosted by
google code but it appears no one is working on it.
Looking at the "R W
Is anyone using rpad? Is there any documentation or examples beyond that in
the 'man' directory of the source?
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anything shorter than as.vector(as.matrix( df ) )?
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R-help@r-project.org ma
If the data is a dataframe or matrix 'd':
d <- d[apply(d, 1, function(v) sum( is.na(v) ) <= 2 & sum(v==0, na.rm=T) <=
2 ), ]
which can be deconstructed as follows:
i1 <- apply(d, 1, function(v) sum(is.na(v)) <= 2 ) ## true for rows with 2
or fewer na's
i2 <- apply(d, 1, function(v) sum( v == 0,
I got tired of writing length(which()) so I define a useful function which I
source in my .Rprofile:
count <- function( x ) length(which(x))
Then:
count( x == 1 )
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Sent from t
27; from DF
> group by groups")
groups wtd mean
1 15
2 2 6
On Tue, Feb 2, 2010 at 5:06 PM, sjaffe <[hidden
email]<http://n4.nabble.com/user/SendEmail.jtp?type=node&node=1461531&i=0>>
wrote:
>
> Thanks! :-)
>
> I suppose it's obvi
Thanks! :-)
I suppose it's obvious, but one will generally have to use a (anonymous)
function to 'unpack' the data.frame into columns, unless the function
already knows how to do this.
I mention this because when I tested the solution on my example I got an
unexpected result -- apparently weig
'fraid not :-((
tapply( data, groups, weighted.mean, weights)
won't work because the *entire* weights vector is passed as the 2nd arg to
weighted.means. But weighted.mean needs 'weights' to be split in the same
way as 'data' -- the first and 2nd args need to correspond.
Jorge Ivan Velez wrot
write.table( rbind( quarter=names(maxr), maxr ), ..., col.names=FALSE, ... )
James Rome wrote:
>
> In my code, I calculate the maximum values with 2 factors using
> maxr=with(arrdf, tapply(rate,list(weekday,quarter), max, na.rm=T))
>
> and I want to write out the file so that Excel can read it
I'm sure I can put this together from the various 'apply's and split, but I
wonder if anyone has a quick incantation:
E.g. I can do tapply( data, groups, mean)
but how can I do something like: tapply( list(data,weights), groups,
weighted.mean ) ?
(or: mapply is to sapply as ? is to tapply )
T
Thanks for the suggestions.
gsub("hello (.*)", "\\1", "hello world")
seems simplest.
Setting value=TRUE returns the whole match, not the subexpression.
(I always read the man pages carefully before asking for help, gratuituous
comments notwithstanding. I didn't see a solution using gregexpr;
What is the simplest way to extract a matched subexpression?
Eg. in perl you can do
"hello world" =~ m/hello (.*)/
which would return 1(true) and set $1 to the matched subexpression "world".
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Even using the example from the documentation:
> f = system.file("exampleData", "size.xml", package = "XML")
> xmlToDataFrame(f, c("integer", "integer", "numeric"))
Called from: xmlToDataFrame(doc, colClasses, homogeneous, collectNames,
nodes = xmlChildren(xmlRoot(doc)))
Browse[1]>
I haven't se
Dieter Menne wrote:
>
> sjaffe riskspan.com> writes:
>
>>
>> I have data with many factors, each taking many values. However, only
>> relatively few combinations appear in the data, ie have nonzero counts,
>> in
>> other words the resulting table is sp
Perhaps this is a common question but I haven't been able to find the answer.
I have data with many factors, each taking many values. However, only
relatively few combinations appear in the data, ie have nonzero counts, in
other words the resulting table is sparse. Say we have 10 factors each wit
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