can be extracted from a given body of
data.
~ John Tukey
-Oorspronkelijk bericht-
Van: stephen sefick [mailto:[EMAIL PROTECTED]
Verzonden: woensdag 3 december 2008 1:09
Aan: ONKELINX, Thierry
CC: hadley wickham; R-help
Onderwerp: Re: [R] ggplot2 facet_wrap problem
If you look at the TSS
Dear Stefan,
Why not use merge() if you want to merge two datasets? ;-)
df1 <- data.frame(A = c(1,2), B = c("m","f"), C = c("at home", "away"))
df2 <- data.frame(A = c(2), C = c("at home"))
merge(df1, df2, all = TRUE)
HTH,
Thierry
--
Try do.call("rbind", aa)
HTH,
Thierry
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics, methodolog
Dear all,
I'm using zeroinfl() from the pscl-package for zero inflated Poisson
regression. I would like to calculate (aproximate) prediction intervals
for the fitted values. The package itself does not provide them. Can
this be calculated analyticaly? Or do I have to use bootstrap?
What I tried u
You're sorting characters in the PHP script instead of numbers!
sort(as.character(o)) in R will yield the same results as you PHP script
does.
Thierry
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Res
Merge both datasets into one with a grouping variable. Then have a look
at the ggplot2 package.
library(ggplot2)
dataset <- data.frame(Month = factor(rep(1:12, 20)), Value =
c(rnorm(120) + 1:12, rnorm(120) + 12:1), Group = gl(2, 120, labels =
LETTERS[1:2]))
ggplot(dataset, aes(x = Month, y
not say. ~William W. Watt
A statistical analysis, properly conducted, is a delicate dissection of
uncertainties, a surgery of suppositions. ~M.J.Moroney
> -Oorspronkelijk bericht-
> Van: ONKELINX, Thierry
> Verzonden: donderdag 4 oktober 2007 17:55
> Aan: '[EMAIL PROTECT
Try somelike this
library(ggplot2)
dow <- data.frame(dayofweek = factor(1:7), p = runif(7), w = c(0, 1, 1,
1, 1, 1, 0))
sc <- scale_fill_continuous()
sc$legend <- FALSE
qplot(dayofweek, p, data=dow, geom="bar", xlab="Day", ylab="Arrival
Rate", main="Spam by Weekday", fill=w) + sc
HTH,
Thierry
-
lijk bericht-
> Van: Christoph Krammer [mailto:[EMAIL PROTECTED]
> Verzonden: maandag 8 oktober 2007 14:35
> Aan: ONKELINX, Thierry; r-help@r-project.org
> Onderwerp: RE: [R] How to remove legend?
>
> Hello Thierry,
>
> thanks for your fast response.
>
>
Have a look at the gstat package and it's documentation.
Thierry
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
Cel biometrie, methodologie en kwaliteitszorg / Sec
Sorry, but I can't help you with your problem isntalling ggplot2. I'm a
WinXP user and have no experience with R on Linux. Maybe Hadley Wickam
could help you out on this one.
Cheers,
Thierry
ir. Thierry Onkelinx
Insti
I use Sweave for this kind of purposes.
HTH,
Thierry
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
Cel biometrie, methodologie en kwaliteitszorg / Section biomet
at they do not say. ~William W. Watt
A statistical analysis, properly conducted, is a delicate dissection of
uncertainties, a surgery of suppositions. ~M.J.Moroney
> -Oorspronkelijk bericht-
> Van: Rainer M Krug [mailto:[EMAIL PROTECTED]
> Verzonden: woensdag 17 oktober 2007 11
> Verzonden: woensdag 17 oktober 2007 14:17
> Aan: ONKELINX, Thierry
> CC: r-help
> Onderwerp: Re: [R] One pdf file with plots and text output
>
> I am getting somewhere - but running system("pdflatex
> GrowthAll") fails, as it does not find sweave.sty. I already
&g
If min and max are two vectors with values on the y-axis and x is a vector of
the values on the x-axis, then you need.
x <- 1:50
z <- matrix(rnorm(100), ncol = 2)
mini <- apply(z, 1, min)
maxi <- apply(z, 1, max)
plot(x, maxi, ylim = range(c(mini, maxi)), type = "l")
lines(x, mini)
polygon(c(x, r
Tom,
Allow me to give a few comments.
x <- c(x=(rep(33:55,1)))
#Is a very uggly way to write
x <- 33:55
#This (untested) code will probably generate a smooth plot too. Maybe
it's not the plot that you intended to create. I'm just guessing as I
can not reproduce your code (because I don't have
apply(matrix, 2, cumsum)
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
methodology and quality
You could work around it like this.
n <- length(levels(TDBU$system))
rows <- ceiling(sqrt(n))
TDBU$rows <- ceiling(as.numeric(TDBU$system) / rows)
TDBU$cols <- (as.numeric(TDBU$system) - 1) %% rows
ggplot(TDBU,aes(x=x))+geom_histogram(aes(y=..density..))+ geom_density()
+ facet_grid(rows ~ cols)
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