similar to: ggplot2 box plot notches

Hi I'm getting a weird result when I try to switch from a normal box plot to a notched one. The ends of the box fold down toward the median giving a horned appearance. Is just the sample itself? It is small, but the un-notched plot looks okay. Anyway to fix this? e7=as.vector(c(234,37,98,116,47)) boxplot(e7, plot=TRUE, notch=TRUE) Thanks very much.

Hello, I'm using the code below to generate some notched box plots. The issue is whenever I use log scale, the sides of the bottom part of the box plots don't plot. I've tried it in RStudio Ver 1.1.419 and R version 3.4.3 and I get the same result. The code and link to my data is below. Thank you for your time David MyData <-

I am having problem making ggplot2, tikzDevice, and knitr working together. I used a very simple example: ---------------------------example.Rnw----------------------------- \documentclass[preview]{standalone} \begin{document} \begin{figure} <<fig1,eval=TRUE,echo=FALSE,dev='tikz'>>= library(ggplot2) qplot(displ, hwy, data = mpg, colour = factor(cyl)) @ \end{figure}

PR #7690 points out that if the confidence intervals (+/-1.58 IQR/sqrt(n)) in a boxplot with notch=TRUE are larger than the hinges -- which is most likely to happen for small n and asymmetric distributions -- the resulting plot is ugly, e.g.: set.seed(1001) npts <- 5 X <- rnorm(2*npts,rep(3:4,each=npts),sd=1) f <- factor(rep(1:2,each=npts)) boxplot(X~f) boxplot(X~f,notch=TRUE) I can

Dear list members, Can anyone tell me how the notches in boxplot(Y~X,notch=T) are calculated? What do these notches represent exactly? I?d suppose they are Conficence Intervals for the median, but I?ve also been told they might show Least Significant Difference (LSD) equivalents. I would very much appreciate any help from you. Best regards Chris.

Sorry to repost this, but it looks like it's getting buried in r-help (originally posted October 5: my experience says that if it hasn't been answered by then it won't be). I wouldn't bother, but I'm worried that r-devel might be better, *and* a previous e-mail of mine on the subject in January also seemed to get buried. Synopsis: boxplot notches look weird when notches are

Dear r-helpers, tst <- data.frame(as.numeric(x <- 1:20), f <- rep(c('hi','lo'), times = 10)) with(tst, bwplot(f ~ x, panel = function(x, y){panel.bwplot(x, y, pch = '|', stats = boxplot.stats, fill = 8, varwidth = T)})) I can't figure out from the documentation how to tell stats that I would like to see notches or (even bands). Here is what I've

Hi, Here are three plots: library(ggplot2) data(diamonds) randind <- sample(nrow(diamonds),1000,replace=FALSE) dsmall <- diamonds[randind,] qplot(carat, data=dsmall, geom="histogram",binwidth=1) qplot(carat, data=dsmall, geom="histogram",binwidth=.1) qplot(carat, data=dsmall, geom="histogram",binwidth=.01) What are ways to put these three plots on a single

Hi All, Can you please help me, why this code in not generating line chart? library(ggplot2) par(mfrow=c(1,3)) #qplot(TIME1, BASCHGA, data=Orange1, geom= c("point", "line"), colour= ACTTRT) unique(Orange1$REFID) -> refid for (i in refid) { Orange2 <- Orange1[i == Orange1$REFID, ] pdf('PGA.pdf') qplot(TIME1, BASCHGA, data=Orange2, geom= c("line"),

Hey hey, I`m analyzing a data set containing the element contentrations of various samples... I wanted to construct notched boxplots and got quite ugly results for some of the boxplots. The notches are often larger then the hinges which resulted in weird looking edges (even though I`m using a log-boxplot). To avoid this problem I thought about using "normal" log-boxplots and adding some

In the area plots below, I see 4 triangle ticks at both sides of the bar; I believe these are non-stacked values for p, but they are definitively confusing. In addition, I would like to get the order of the colors in the plot the same as in the legend, and not arranged alphabetically (the factor is ordered, don't touch my order). Hadley once mentioned an undocumented aestetics

Hello, this following code give a nice png: /library(ggplot2) i <- 1 png(file=paste('test ',i,'.png',sep='')) qplot(carat, data=diamonds, fill=color,geom='histogram')+scale_y_continuous(i) dev.off() / I would like to get more files, but the following code doesn't make any file: /library(ggplot2) for (i in 1:2) { png(file=paste('test

Hi, ggplot/qplot is great - it has really helped me do some nice things. However, simple boxplot of different columns/variables is a bit tricky, because of (i think) qplot's generic Y conditional on X input form. Se below. # Some data: a <- rnorm(100) b <- rnorm(100,1,2) c <- rnorm(100,2,0.5) # normal boxplot of a,b,c boxplot(a,b,c) # Looks good library(ggplot2) # loads qqplot2 #

Hi, I'm trying to create a stacked bar plot using ggplot2. Rather than plotting the count of each of the 13 "Bar" factors on the Y axis, I would like to represent the sum of the Values associated with each of the 13 "Bar" factors. Is there a way to do that? Given the following data, that would obviously mean that there would be some negative sums represented. Here's

HI am plotting different density plots in one graph each with a different color. And i want to add labels to plot mentioning which color belongs to which data series. p2 <- qplot(corArms, data = data1, geom = "density", adjust=0.4, main="Arms Correlation All") + layer(data=data2, geom="density", adjust=0.4, color=I(2)) + layer(data=data3,

Hi Folks, First, the important information. > sessionInfo() R version 2.12.1 (2010-12-16) Platform: i386-pc-mingw32/i386 (32-bit) Second, my problem. I have a series of data sets comprised in the following format. > totsoc Location Year Value 1 SOUTH 1998 29 2 SOUTH 1999 20 3 SOUTH 2000 32 4 SOUTH 2001 29 5 SOUTH 2002 25 6 SOUTH 2003 28 7

Hello all, I'm stuck with a strange issue with writing jpegs of plots to a folder in a loop. This works: for (step in 1:length(steps)) { jpeg(filename=paste("frame_",sprintf("%05d",step),".jpg",sep="")) plot(steps[[step]]) dev.off() } But if I use qplot to generate the plot (which is my aim): for (step in 1:length(steps)) {

In the help for scale_fill_identity, it is written ## Not run: colour <- c("red","green","blue","yellow") qplot(1:4, 1:4, fill=colour, geom="tile") qplot(1:4, 1:4, fill=colour, geom="tile") + scale_fill_identity() # To get a legend, you also need to supply the labels to # be used

I am using ggplot2 to make a boxplot that overlays a scatterplot: pp = qplot(time, error, data=times, size=I(1), geom="jitter", main=title, ylab="Error (min)", xlab="Time before ON (min)", alpha=I(1/10), color=times$runway, ylim=c(-30,40)) pp2 = pp + with(times, facet_wrap(~ runway, ncol=2)) print(pp2 + geom_boxplot(alpha=.5,

Dear list, I wish to plot chromatin precipitation data: I would like to have a rectangles (x:end-start, y:peak) but I do not have an idea how to define x (in terms of qplot syntax) and to choose the correct geom. mydata is a subset of a larger file. > mydata chrom start end peak 1 chr11 5291000 5291926 8 2 chr11 10988025 10988526 7 3 chr11 11767950 11768676 8 4