similar to: ggplot and xlim/ylim

Hi everyone, Hi ggplot users in particular, ggplot makes it very easy to plot things given their names when you use it interactively (and therefore can provide the names of the columns). qplot(x,foo,data=A) where A has columns (x,y,foo,bar) for example but I would like to use this from inside a function to which the name of the column is given. I cannot find an elegant way to make this

Hello everybody, This is probably a classic but I cannot find an answer to this on the mailing list (i.e. with a google search restricted to the mailing list archive). Setting: par(new=T) plot(x,y) works but plot(x,y,new=T) doesn't while it is said in plot's help that ... arguments are passed to par. What am I missing? JiHO --- http://jo.irisson.free.fr/

Hello everyone (and Hadley in particular), I often need to plot data from multiple datasets on the same graph. A common example is when mapping some values: I want to plot the underlying map and then add the points. I currently do it with base graphics, by recording the maximum region in which my map+point will fit, plotting both with these xlim and ylim parameters, adding par (new=T)

Hello everyone, A recent (in 2.5 I suspect) change in R is giving me trouble. I want to apply a function (tolower) to all the columns of a data.frame and get a data.frame in return. Currently, on a data.frame, both apply (for arrays) and lapply (for lists) work, but each returns its native class (resp. matrix and list): apply(mydat,2,tolower) # gives a matrix lapply(mydat,tolower) # gives

Hello all, I discovered that the pdf device uses fonts to represent "points" symbols (as in plot(...,type="p",...) ). Namely it uses ZapfDingbats with symbol U+25cf. This can lead to problems when the font is not available, or available in another version (such as points being replaced by other symbols, or worst: slightly displaced). Furthermore, it also causes

Dear List, I am trying to get R's terminal output to a file and to the terminal at the same time, so that I can walk through some tests and keep a log concurrently. The function 'sink' with the option split=TRUE seems to do just that. It works fine for most output but for objects of class htest, the terminal output is incomplete (the lines are there but empty). Here is an

Hello, I am facing a problem with lapply which I ''''think''' may be a bug. This is the most basic function in which I can reproduce it: myfun <- function() { foo = data.frame(1:10,10:1) foos = list(foo) fooCollumn=2 cFoo = lapply(foos,subset,select=fooCollumn) return(cFoo) } I am building a list of dataframes, in each of which I want to keep only column

Hi everyone, Hi Hadley, I am a heavy user of coord_equal() in ggplot2 since most of my data is spatial, on x,y coordinates. Everything works. However by enforcing an aspect ratio of 1 for the plotting region, coord_equal() usually wastes a lot of space if the region of interest is not a perfect square. For example: x=runif(10) a=data.frame(x=x*3,y=x) ggplot(data=a, aes(x=x,y=y)) +

Hello everyone, I often create some local "libraries" of functions (.R files with only functions in them) that I latter call. In scripts that call a function from such library, I would like to be able to test whether the function is already known in the namespace and, only if it is not, source the library file. I.e. what `require` does for packages, I want to do with my local

Hello everyone, I have two data.frames that look like calib: place zoom scale left 0.65 8 left 0.80 5.6 left 1.20 3 right 0.65 8.4 right 0.80 6 right 1.20 2.9 X: ... place zoom .... ... left 0.80 .... ... left 1.20 .... ... right 0.65 .... ... NA NA .... ... right 0.8 .... ... left 1.20 .... and I want to get the corresponding values of 'scale' in a new column

Hello eveybody, I am studying the vertical distribution of plankton and want to study its variations relatively to several factors (time of day, species, water column structure etc.). So my data is special in that, at each sampling site (each observation), I don't have *one* number, I have *several* numbers (abundance of organisms in each depth bin, I sample 5 depth bins) which

Hello all, I am sure I am missing something obvious but I cannot find the function I am looking for. I have a data frame with three columns: X, Y and Z, with X and Y being grid coordinates and Z the value associated with these coordinates. I want to transform this data frame in a matrix of Z values, on the grid defined by X and Y (and, as a plus, fill the X.Y combinations which do no

Dear Lists, At several stations distributed regularly in space[1], we sampled repeatedly (4 times) the abundance of organisms and measured environmental parameters. I now want to compare the spatial distribution of various species (and test wether they differ or not), or to compare the distribution of a particular organism with the distribution of some environmental variable.

The model frame shows the response and predictors in a data frame with nicely labelled columns: fm <- lm(wt~qsec+log(hp)+sqrt(disp), data=mtcars) model.frame(fm) # ok When the left hand side consists of more than one response, those response variables still look good, inside a matrix: fm <- lm(cbind(qsec,hp,disp)~wt, data=mtcars) model.frame(fm)[[1]] # ok A problem arises when

The function wtd.var(x,w) in Hmisc calculates the weighted variance of x where w are the weights. It appears to me that wtd.var(x,w) = var(x) if all of the weights are equal, but this does not appear to be the case. Can someone point out to me where I am going wrong here? Thanks. Tom La Bone [[alternative HTML version deleted]]

is it possible to map 2 plots(c and d) in a single output plot? library(ggplot2) c <- ggplot(mtcars, aes(qsec, wt)) d <- ggplot (mtcars, aes(qsec, wt)) c + stat_smooth(fill="darkgrey", colour="blue", size=2, alpha = 0.2) d + stat_smooth(fill="darkgrey", colour="red", size=2, alpha = 0.2) -- View this message in context:

I think you are not using the best function for what your intentions are. Try: > by(data=mtcars, INDICES=list(as.factor(mtcars$am)), FUN=colMeans) : 0 mpg cyl disp hp drat wt qsec vs 17.1473684 6.9473684 290.3789474 160.2631579 3.2863158 3.7688947 18.1831579 0.3684211 am gear carb 0.0000000

Hi, I went ahead and implemented something. However: - I cannot garantie it gives correct results since, unfortunately, the data used in Syrjala 1996 is not published along with the paper. To avoid mistakes, I started by coding things in a fast and simple way and then tried to optimize the code. At least all versions given the same results. - As expected, the test is still quite slow

Hii i have been trying to do a scatter plot with ggplot2, like the plot 6 here (http://had.co.nz/ggplot2/geom_point.html) .. where the points size vary with values > p + geom_point(aes <http://had.co.nz/ggplot2/aes.html>(size = qsec)) but am not sure how to setup the parameter - qsec could anyone please give some pointers on how to define that thanks Mo. [[alternative HTML

Hola, Bueno, puedes hacer el cálculo de una forma mucho más compacta y rápida. Esta forma es especialmente recomendable cuando tienes muchas columnas y muchas filas. > library(data.table) > myDT <- as.data.table(mtcars) > myDTlong <- melt(myDT, measure.vars=1:ncol(myDT)) > myDTlong[ , list(p_value = shapiro.test(value)$p.value, v_stat = shapiro.test(value)$statistic) , by