See ?merge.
df.1 <- data.frame(year=factor(rep(1:3,3)), level=rep(letters[1:3],3),
number=c(11:19))
df.2 <- data.frame(year=factor(c(1:5)), number=c(21:25))
df.3 <- merge(df.1, df.2, by = "year")
df.3$new <- with(df.3, number.x + number.y)
Jeremy
On Wednesday, April 27, 2011 7:30:13 AM UTC-
See ?on.exit
Jeremy
On Wednesday, April 27, 2011 9:16:13 AM UTC-4, Jannis wrote:
>
> Dear list members,
>
>
> is it possible to set some options only inside a function so that the
> original options are restored once the function is finished or aborted due
> to an error? Until now I do someth
Vincy,
In addition to the R-help mailing list, other forums for R and statistics
that I go to include:
Stackoverflow's R tagged questions
http://stackoverflow.com/questions/tagged/r
StackExchange's Stats site:
http://stats.stackexchange.com/
A Google search for R statistics forum shows a few o
Hans,
You could parallelize it with the multicore package. The only other thing I
can think of is to use calls to .Internal(). But be vigilant, as this might
not be good advice. ?.Internal warns that only true R wizards should even
consider using the function. First, an example with .Intern
= circumference, group=Tree))
# Specify the geom_point and geom_line colour aesthetics as group
g1 + geom_point(aes(colour = group)) + geom_line(aes(colour = group))
Is this what you are after?
Jeremy
Jeremy Hetzel
Boston University
[[alternative HTML version deleted]]
As I understand it, you are trying to subset the data frame to include only
rows with a non-unique id.
Try this:
x <- data.frame(cbind(id=c(1,2,2,2,3,3,4,5,6,6), value=1:10))
id.table <- table(x$id)
x_new <- subset(x, id %in% id.table[id.table > 1])
Jeremy
___
Sorry, I left out the names() function in the last step.
Try this instead:
x <- data.frame(cbind(id=c(1,2,2,2,3,3,4,5,6,6), value=1:10))
id.table <- table(x$id)
x_new <- subset(x, id %in% names(id.table[id.table > 1]))
Jeremy
__
R-help@r-project.org mai
If you are just looking to collapse the dummy variables into two factor
variables, the following will work.
## Generate some example data
set.seed(1234)
n <- 100
# Generate outcome
outcome <- rbinom(n, 3, 0.5)
colnames(exposures) <- paste("V", seq(1:10), sep = "")
#Generate dummy variables for A
imtest$eth, unique(simtest$eth), "==") + 0
# Combine
simtest.combined <- cbind(simtest, simtest.dichotomous)
head(simtest.combined)
Jeremy
Jeremy Hetzel
Boston University
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mail
Scribus claims to be able to convert RGB/CMYK colors to spot colors:
http://documentation.scribus.net/index.php/Spot_Colors
I've never used Scribus, but it's floss.
Jeremy
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
By the way, I had trouble importing PDFs into Scribus 1.3.3. However,
Scribus 1.4.0rc3 had no problem opening multi-page PDFs, assuming the
appropriate Ghostscript was also installed (I'm on Windows 7 at the moment).
So Matthieu might be able to combine all of his figures into a single PDF,
c
Kevin,
The following follows John's suggestion, but without the loop. It's quick
for me.
Jeremy
Jeremy T. Hetzel
Boston University
## Generate sample data
n <- 4000
rep <- 1000
rate <- rnorm(n, mean = 15, sd = 2) / 10 # Mortality rates around
15/100k
## Create an empty matrix with ap
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