similar to: ggplot question

Hi R experts, I have a data recoding problem I cant get my head around - I am not that great at the subsetting syntax. I have a dataset of longitudinal toxicity data (for multistate modelling) for which I want to also want to do a simple Kaplan-Meier curve of the time to first toxic event. The data for 2 cases presently looks like this (one with an event, the other without), with id representing

Hi all, I want to create a simple plot with 2 type='s' lines on it: plot(a, b, type='s') lines(x, y, type='s') I wish to then fill the area between the curves with a colour to accentuate the differences eg col=gray(0.95). I cant seem to come up with a simple method for this. Any pointers in the right direction much appreciated. Cheers Scott

I have a large dataset similar to this: ID time result A 1 5 A 2 2 A 3 1 A 4 1 A 5 1 A 6 2 A 7 3 A 8 4 B 1 3 B 2 2 B 3 4 B 4 6 B 5 8 I need to extract a number of features for each individual in it (identified by "ID"). These are: * The lowest result (the nadir) * The time of the nadir - but if the nadir level is present at >1 time point, I need the minimum and maximum time of nadir

Dear list members, I am looking for a goodness of test that will tell me if a sample is likely to have come from a standard normal distribution. I can find plenty of omnibus tests for normality in the nor.test package, but none of them appear to allow me to test against the specific alternative that the data are not standard normal. My back up option is to use a Kolmogorov-Smirnov test, but my

Hi all, I am trying to get bootstrap resampled estimates of covariates in a Cox model using cph (Design library). Using the following I get the error: > ddist2.abr <- datadist(data2.abr) > options(datadist='ddist2.abr') > cph1.abr <- cph(Surv(strt3.abr,loc3.abr)~cov.a.abr+cov.b.abr, data=data2.abr, x=T, y=T) > boot.cph1 <- bootcov(cph1.abr, B=100, coef.reps=TRUE,

Hi all, I was trying to draw a stacked density plot like that : library(ggplot2); library(plyr) dat <- cbind(rnorm(300), rep(c(1,2), each=150)) ggplot() + geom_density(aes(x=dat[,1], fill=factor(dat[,2]), position="stack")) + xlab("") + ylab("") + scale_colour_manual(name = "Pallet", labels = c("X", "Y")) Here

Hi, I used the command ggplot as follows... p<-ggplot(a,aes(x=a$V1,colour=a$V2,fill=a$V2)) p + geom_density(alpha = 0.2,xlim=c(-10,10),ylim=c(0,0.5)) when I say, dev.print(device=postscript,file="/alpha/dct.pdf") I get Warning message: In grid.Call.graphics("L_polygon", x$x, x$y, list(as.integer(1L:length(x$x)))) : semi-transparency is not supported on this device:

> Hi, > I recently downloaded R on window and running Rgui on NT. I have never use > R before and trying to learn R by following An introduction to R. > I generated a table of 900x5 in excel and saved as tab delimited txt file. > I then do read.table but I keeping getting the following message > > data <- read.table("ML4mm25.txt", header=T, sep=" ")

Dear all, I do not fully understand how ggplot2 handles NAs. See the following example: library(ggplot2) x <- rnorm(150) g <- as.factor(c(rep(c(0,1,NA),50))) mydf <- data.frame(x,g) m <- ggplot(aes(x = x, group = g, color = g), data = mydf) m + geom_density() How do I get rid of the NAs (i.e. the blue colored curve)? I thought ## m <- ggplot(aes(x = x, group = g, color = g,

Dear All, Further to answers to sorting, can someone tell me how can I sort a list that contains duplicates (name) but keeping the duplicates together when sorting the values. e.g., a data frame with name (in duplicates), Mvalues(may be different for the duplicates) name M 1234 8 1234 8.3 4321 9 4321 8.1 If I sort by M, it will be 1234, 4321, 1234, 4321 but I want to keep the duplicates together,

I am learning ggplot2 commands and I have figured out how to create histograms and density curves but I am not sure how to add a density curve on top of a histogram. Here are the two graphs that I created. ## Histogram t<-rnorm(500) w<-qplot(t, main="Normal Random Sample", fill=I("blue"), colour=I("black"), geom="histogram") w ##Density Curve

Dear all, For two sets of random variables, say, x <- rnorm(1000, 10, 10) and y <- rnorm(1000. 3, 20). Is there any way to overlay the histograms (and density curves) of x and y on the plot of y vs. x? The histogram of x is on the x axis and that of y is on the y axis. The density curve here is to approximate the shape of the distribution and does not have to have area 1. Thank you

Hi all, I am trying to plot a weighted density plot for two different types and want to show the data points on the x axis. The code is as follows. The data points are very concentrated. Is there a better way to present it( should I set the alpha value or something else)? Thanks! YL library(ggplot2) x <- rnorm(10000) a <- rnorm(5000) b <- rnorm(5000) weights.x <- abs(a/sum(a))

I have a data that looks like this: http://dpaste.com/88561/plain/ And I intend to create multiple density curve into one plot, where each curve correspond to the unique ID. I tried to use "sm" package, with this code, but without success. __BEGIN__ library(sm) dat <- read.table("mydat.txt"); plotfn <- ("~/Desktop/flowgram_superimposed.pdf"); pdf(plotfn);

Hi I'm just starting off with R but is this correct? I have this data set. > data Type ID Size 1 Reqd 244808 1024 2 Reqd 244045 512 3 Reqd 245427 800 4 Reqd 245423 1024 5 Reqd 244983 1024 6 Used 244808 615 7 Used 244045 33 8 Used 245427 261 9 Used 245423 461 10 Used 244983 1194 I want a scatterplot of the Size values grouped by the Type column. I also want 2 lines

Does anyone (Hadley??) know if there's a straightforward way in ggplot2 to get data divided by a single factor to plot as a rectangular grid of subplots? So far I've only been able to get such data plotted as a single row or single column of skinny subplots. The code below gives an example implemented with lattice, and my best attempt in ggplot2 cheers Ben Bolker ------------ g=

#After spending the entire day working on this question, I have decided to reach out for support: #I am trying to overlay a densityplot from one data set over a histogram of another, if I were to plot the two individually, they would look like: # data frame construction data.frame.A <- data.frame(rnorm(12*8), c(rep("one", 4), rep("two", 4), rep("three", 4)),

Hi R-help I'm trying to create a grid plot in which each plot in the grid contains two density plots (colored by factor) and two vertical lines at the respective medians (also colored by the factor). Using the diamonds dataset as an example, the following commands give me price density plots by factor cut in a single, ungridded plot. p <- ggplot(data=diamonds, aes(x=price)) +

Buenas tardes, tengo una variable bimodal (*var)*, de presencias y ausencias (1s y 0s) y otra variable, *prob*, con las probabilidades que le asigna un modelo (entre 0 y 1). Con: *ggplot(Preds, aes(x=prob, fill= var )) + geom_density(alpha=.3)* obtengo la distribución de las presencias y de las ausencias, por separado, en función del valor de probabilidad asignado. Las dos curvas se cruzan en un

Text is really small and legend boxes are huge in this plot when saved to .png with ggsave. Plot is correct (i.e. looks the same as the screen) when saved with dev.print. Saving to .pdf with ggsave give the correct output. I'm a noob at ggplot2 so this may be user error rather than a bug. However the interface to ggsave seems simple enough to exclude many possibilities for screwing this up