search for: geom_density

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, na.rm = TRUE), ## data = mydf) ## m + geom_density() or ## m <- ggplot(aes(x = x, group = g, color = g), data = mydf) ## m + geom_density() ## m + stat_density(na.rm =...

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

...hts.y <- abs(b/sum(b)) weight <- c(weights.x, weights.y) ze <- rep(0,10000) type <- c(rep("a",5000), rep("b",5000)) d <- data.frame(expo = x, weight = weight, type = type, ze = ze) m <- ggplot(d, aes(x = expo, group = type, col = type, weight = weight)) m+geom_density()+geom_point(aes(x = expo, y = ze, shape = type))

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: reported only o...

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

...each with an alpha =0.25). I have tried a number of variations of the following, but cannot find a way to define the colour of the fill, its transparency and the line around it individually - something in the syntax continues to defy me. ggplot(data.plot, aes(x=x, y=..density..))+ geom_density(aes(group=group)) I am sure a simple solution is out there. Any help appreciated, Scott _____________________________ Dr. Scott Williams MBBS BScMed FRANZCR Radiation Oncologist Peter MacCallum Cancer Centre Melbourne, Australia ph +61 3 9656 1111 fax +61 3 9656 1424 scott.will...

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 everything is ok, except few points : 1. I want to remove the name of y-...

...x | system, data = TDBU, xlab = "LRR Effect Size",type="density", panel = function(x, ...) { panel.histogram(x, ...) panel.densityplot(x,...) } ) library(ggplot2) ggplot(TDBU,aes(x=x))+geom_histogram(aes(y=..density..))+ geom_density()+facet_grid(system~.) -- View this message in context: http://www.nabble.com/ggplot2-facets-as-rows-and-columns-tf4771000.html#a13647294 Sent from the R help mailing list archive at Nabble.com.

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);

...wo 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)) + geom_density(aes(color=cut)) p I can add vertical lines at the medians of each density as follows. medians <- data.frame(cut=levels(diamonds$cut), intercept=tapply(diamonds$price, list(diamonds$cut), median)) p + geom_vline(data=medians, aes(color=factor(cut))) I can create a gridded plot of price dens...

#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)),

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 punto. ¿Sabéis si hay forma de averiguar el valor de *prob* de ese punto analíticamente? Gracias, Manuel [image: image.png] ---------...

...p through ignorance. We'll see I guess. Here's the example. require(ggplot2) x <- data.frame(value=rnorm(5000, mean=0), case="A") y <- data.frame(value=rnorm(5000, mean=3), case="B") xy <- rbind(x, y) p <- ggplot(xy, aes(x=value, colour=case, group=case)) + geom_density() p ggsave(p, filename = "xy_ggsave.png") dev.print(device=png, width=600, height=600, file="xy_devprint.png") ggsave(p, filename = "xy_ggsave.pdf") dev.print(device=pdf, file="xy_devprint.pdf") -- View this message in context: http://www.nabble.com/gg...

...VI ALLA DATA PUNKTER ###### ggplot(data=tryck, aes(tryck[,1])) + geom_histogram(aes(y =..density..), breaks=seq(min(tryck[,1]-1), max(tryck[,1]+1), by = 0.5), col="black", fill="green", alpha = .2) + geom_density(col=2) + labs(title="Pressure for r?dmans?") + labs(x="Pressure [kPa]", y="Amount of vehicles (Percentage)")+ stat_function(fun=dnorm, colour="blue", args = list(mean = mean(tryck[,1]), sd = sd(tryck[,1]))) My problem now is to find a statistical...

...r * geom_boxplot: now has it's own legend which actually looks like a boxplot * geom_boxplot: reports if missing values removed * geom_crossbar: the middle line is now display thicker than the other lines, controlled by the parameter fatten (thanks to Heike Hofmann for the suggestion) * geom_density: fix scale adjustment bug in geom_density * geom_line, geom_text: all size measurements (now lines and text as well) are measured in mm, lines/paths default to paths 0.5mm wide * geom_rug: new to add marginal rug plots * geom_smooth: added example showing how to use geom_smooth with your own...

...r * geom_boxplot: now has it's own legend which actually looks like a boxplot * geom_boxplot: reports if missing values removed * geom_crossbar: the middle line is now display thicker than the other lines, controlled by the parameter fatten (thanks to Heike Hofmann for the suggestion) * geom_density: fix scale adjustment bug in geom_density * geom_line, geom_text: all size measurements (now lines and text as well) are measured in mm, lines/paths default to paths 0.5mm wide * geom_rug: new to add marginal rug plots * geom_smooth: added example showing how to use geom_smooth with your own...

...ve read the density plot help and noticed the reference to ..density.. as a means to pass density data instead of original data. But I can't seem to get a boxplot to overlay a density plot. This is what I've got so far with consequent error message: m <- ggplot(mydata, aes(x=VALUE)) m + geom_density()+ geom_boxplot(aes(x=..density..)) Error in data.frame(..., check.names = FALSE) : arguments imply differing number of rows: 0, 180 I've tried y=..density.., both x= and y = ..density.. and neither and all fail somehow. Problem is I don't really understand what I'm doing at this...

d <- structure(list(Site = structure(c(8L, 12L, 7L, 6L, 11L, 5L, 10L, 4L, 3L, 2L, 1L, 9L, 8L, 12L, 7L, 6L, 11L, 5L, 10L, 4L, 3L, 2L, 1L, 9L, 8L, 12L, 7L, 6L, 11L, 5L, 10L, 4L, 3L, 2L, 1L, 9L, 8L, 12L, 7L, 6L, 11L, 5L, 10L, 4L, 3L, 2L, 1L, 9L, 8L, 12L, 7L, 6L, 11L, 5L, 10L, 4L, 3L, 2L, 1L, 9L, 8L, 12L, 7L, 6L, 11L, 5L, 10L, 4L, 3L, 2L, 1L, 9L, 8L, 12L, 7L, 6L, 11L, 5L, 10L, 4L, 3L, 2L, 1L, 9L,

...re identifiable) now work correctly * all ggplot objects should now print properly from the command line * fixed bug in geom_path when only 1 point * segments geom now works correctly for more coordinate systems * order variables in scatterplot matrix by order of variables in data.frame * geom_density deals with missing values correctly when displaying scaled densities * fixed bug in calculating categorical ranges * fixed bug in drawing error bars Subtractions * now relies on R 2.6 * removed grid.gedit and grid.gremove, and code replaced by grid.ls -- http://had.co.nz/ _____________...

...re identifiable) now work correctly * all ggplot objects should now print properly from the command line * fixed bug in geom_path when only 1 point * segments geom now works correctly for more coordinate systems * order variables in scatterplot matrix by order of variables in data.frame * geom_density deals with missing values correctly when displaying scaled densities * fixed bug in calculating categorical ranges * fixed bug in drawing error bars Subtractions * now relies on R 2.6 * removed grid.gedit and grid.gremove, and code replaced by grid.ls -- http://had.co.nz/ _____________...