similar to: black and white in qplot? layout 4 graphs in one screen

Hello, I want to arrage the label according to my preference eg.. (va, vp, a, b, c) but don't know how to supress default ordering. Any suggestions? Please try the code below: n <- c("va", "vp", "a", "b", "c") p <- c(2, 2,1, 3,5) pm<- c(3,4,2,5,4) pn <- c(1,1,1,2,3) x<-data.frame(cbind(n,p,pm,pn)) library(ggplot2) qplot(x=n,

Hello, I am a new r-user, and after a great effort I have made this fantastic figure with qplot: qplot(ROI, CBF, fill=factor(Carrier), data=combinedboxplot_dataset_se_1_CBF, geom="boxplot", position="dodge",xlab=NULL,ylab=("CBF,white matter-normalized"),main=("Differences between carriers and non-carriers on baseline"))+theme_bw() Can anyone help me

I'm having problems with this example, it is posted with reproduceable code below, both with the normal 0-6 scale and the desired 3-6 scale (with bars removed). How can I get the graph to have the desired 3-6 scale without removing the bars. Thanks! #Data

I was wondering if anyone could help me with this, simple problem. I am essentially following the example on Hadley's webpage (http://had.co.nz/ggplot2/geom_errorbar.html), but it still doesn't make any sense to me. df <- data.frame(trt = factor(c("intact", "intact", "removed", "removed")), coon = c(0.093, 0.06, 0.057, 0.09), group =

Dear List, (self-contained example + version info at the bottom) I'm having trouble producing a barplot using the functions in ggplot2. When I use the position="dodge" option, the bars are plotted but also a number of spurious markers. More specifically, a number of black dots are plotted in the graph that should not be there. This behaviour is not seen when calling the same

Hello HelpeRs, The last print statement in the code segment below results in : Error in data$x[data$x == -Inf] <- range$x.range[1] : replacement has length zero R version 2.14.1 Patched (2011-12-23 r57982) ggplot2: version 0.90 OS : Linux (64bit) Any thoughts? Many Thanks, A. ## code segment starts here df <- data.frame( trt = factor(c(1, 1, 2, 2)), resp = c(1, 5,

Hello again, everytime I think I got something to work, the next issue comes up... I have the following data.frame, I want to visualize: > data_rb tld spam1 spam2 share 1 ca 826436 73452 0.0889 2 org 470550 25740 0.0547 3 de 156042 15531 0.0995 4 com 140753 7527 0.0535 5 edu 34845 2507 0.0719 6 net 12781 382 0.0299 7 ru 7648 18 0.0024

Hi, I wanted to generate a plot which is almost like the plot generated by the following codes. category <- paste("Geographical Category", 1:10) grp1 <- rnorm(10, mean=10, sd=10) grp2 <- rnorm(10, mean=20, sd=10) grp3 <- rnorm(10, mean=15, sd=10) grp4 <- rnorm(10, mean=12, sd=10) mydat <- data.frame(category,grp1,grp2,grp3,grp4) dat.m <- melt(mydat) p <-

Is this what you want? temp<-c(rep("Low",2),rep("Medium",2),rep("High",2)) light<-rep(c("Dark","light"),3) avg<-dat.avg2[,3] # se<-dat.avg2[,4] dat.avg.temp<-data.frame(cbind(avg,se)) dat.avg.temp<-data.frame(cbind(temp,light,dat.avg.temp)) dat.plot<-qplot(light,avg, fill=factor(temp),data=dat.avg.temp, geom="bar",

Hi, Please consider the example below. How can I manage to overlay the points the way I want in the second case? Thanks, Joh library(ggplot2) # Modify data to match "real" case myDiamonds <- diamonds myDiamonds[["clarity"]] <- as.character(myDiamonds[["clarity"]]) myDiamonds[myDiamonds[["clarity"]]=="I1","clarity"] <- 1

Like this? # example using qplot library(ggplot2) meanprice <- tapply(diamonds$price, diamonds$cut, mean);meanprice cut <- factor(levels(diamonds$cut), levels = levels(diamonds$cut)) qplot(cut, meanprice, geom="bar", stat="identity", fill = I("grey50")) dev.new() # create a new graph to compare with qplot # Example using ggplot ggdata <-

Hi All, I have trying to do what I thought was a reasonably simple graph but I think I'm now going in circles with the colour. Attached is a picture of where I'm up to. The line creating this is: qplot(ageincgraph$age, ageincgraph$rate, position="dodge", stat="identity", geom="bar" ) + aes( colour=ageincgraph$era) +

Hi all: Using the example below, is there a way to add Y axis titles to each graphic instead of sharing the same title? library(ggplot2) RT = matrix(c(814, 500, 424, 394, 967, 574, 472, 446),4,2) colnames(RT) = c('repetition','alternation') rownames(RT) = c('7-yrs','11-yrs','15-yrs','21-yrs') rt <- melt(RT) names(rt) <- c("age",

Hi, Could anyone give suggestions how to plot a scatter plot with 1 standard deviation for each point. To make it clearer, here is a simple example: the scatterplot is plot(X, Y), but I want to add 1 standard deviation according to the value of Z for each Y. X Y Z 1 3.5 1.1 . . . . . . . . . Thanks a lot in advance. FD [[alternative HTML

Hi, I have the following data: > Myvalues Gene ES MEF Embryo ESHyp 1 GeneA -0.38509507 0.00 1.6250 1.7039921 2 GeneB 0.06262914 0.00 1.6250 -0.272033 and so on... I want to plot the expression values of GeneA and GeneB in the different cell/embryo/conditions (columns 2:5 above). Now, if I do: >library(ggplot2) > qplot(x=Gene, Embryo, geom =

Dear List, I just googled to find out if notched box plots are possible with ggplot2, but couldn't find a answer to it. boxplot() has the option: notch = TRUE, e.g.: boxplot(mpg$hwy, notch=TRUE) My example code (taken from the net) is: require(ggplot2) qplot(class, hwy, fill=factor(year), data=mpg, geom="boxplot", position="dodge")+theme_bw() Thank you for you help!

Hi All, I am frustrated by mixed-effects model! I have searched the web for hours, and found lots on the nested anova, but nothing useful on my specific case, which is: a random factor (C) is nested within one of the fixed-factors (A), and a second fixed factor (B) is crossed with the first fixed factor: C/A A B A x B My question: I have a functioning model using the aov command (see

I have been working on the following code but keep getting an err message. My current thinking is that the problem is on the indexing but do not know how to fix it. Any help please? ungulate <- read.csv("Ungulate.csv",row.names=1) ungulate <- as.matrix(ungulate);colnames(ungulate)<-NULL;rownames(ungulate)<-NULL habitat <- read.csv("Ungulate_vegetation.csv")

Dear listers, I am trying to assess variance components for a nested, mixed-effects model. I think I got an answer that make sense from R, but I have a warning message and I wanted to check that what I am looking at is actually what I need: my data are organized as transects within stations, stations within habitats, habitats within lagoons. lagoons: random, habitats: fixed the question is:

Hi, there I first sent this e-mail a couple months ago, to no avail.Since I am not a member on your mailing list, so could you please cc: a response to me? I'll be sure to check the list today for replies. I am currently attempting to perform an ANOVA with both nested and normal factors. My problem is that R is treating my nested factors the exact same way as it would interaction terms.