similar to: ggplot, ribbon not showing up properly

Any help with this problem would be greatly appreciated: I need to produce a custom plot i haven't come across in R. Basically, I want to show means, 1st standard deviation and 5th and 95th percentiles visually, using something resembling a boxplot. Is it possible to completely customize a boxplot so that it shows means as the bar (instead of, not as well as medians), standard deviations at

Dear List, I am having trouble setting the transparency of a ribbon in ggplot2 and was wondering if anybody had any suggestions so far i have a plot exactly as i want it and i want to add a ribbon connecting the ymax and ymin, whci i do with the following command m10 + stat_summary(geom="ribbon", fun.ymin="min", fun.ymax="max") However the ribbon is a dark grey

The following script is written by the author of a book on R--Andy Field: You can also download the small datafile, hiccups.dat, from this address: http://www.sagepub.com/dsur/study/articles.htm The script: hiccupsData <- read.delim("Hiccups.dat", header = TRUE) hiccups<-stack(hiccupsData) names(hiccups)<-c("Hiccups","Intervention")

Dear All, I am trying to graph a simple scatter plot where the x axis is year and the y axis is a percentage (percentage of infant death). Instead of plotting the raw data, I want to plot summary statistics such as mean and median. Here is the problem: the value range of y is between 0 and 1, but since infant death is a rare event, the mean and median is very low (something like 5%), which shows

I get the following error when I run qplot() qplot(grade, read,data = hhm.long.m, geom = c("point", "smooth")) Error in smooth.construct.cr.smooth.spec(object, data, knots) : x has insufficient unique values to support 10 knots: reduce k. I am not sure how to tackle this problem. When I take a subsample (< 1000) than I am able to run that function but with my sample

Hello, I'd like to produce a ggplot where the order of factors within facets is based on the average of another variable. Here's a reproducible example. My problem is that the factors are ordered similarly in both facets. I would like to have, within each facet of `f1', boxplots for 'x' within each factor `f2', where the boxplots are ordered based on the average of x

Dear all, I produced the following graph with ggplot which is almost fine, yet I don't like that the legend for "Means" and "Observations" includes a line, though no line is used in the plot for those two (the line for "Overall Mean" on the other hand is wanted): library(ggplot2) ddf <- data.frame(x = factor(rep(LETTERS[1:2], 5)), y = rnorm(10)) p <-

Hi All, Here is the code that I'll be referring to: p <- ggplot(wastran.data, aes(PER_KEY, EVENTS)) (p <- p + facet_grid( pool.short ~ .) + stat_summary(aes(y=EVENTS), fun.y = sum, geom="line") + opts(axis.text.x = theme_text(angle = 90, hjust=1), title="Events (15min.) vs. Time: Facet pool", strip.text.y = theme_text()) ) Now, depending on preceding

Buenas, En R, como en la mayoría del software estadístico, no se utiliza ningún nivel de confianza sino que lo que se calcula es el p-valor asociado al contraste. De forma que cuanto más cerca de 0 esté el p-valor "menos credibilidad le damos a la hipótesis nula". Dicho mejor, debemos rechazar la hipótesis nula si el p-valor está por debajo de nuestro nivel de confianza. Por ejemplo,

Hii, I created some boxplots with this commands: x <-read.table(file="test.txt") x$group <- rep(1:8, each=5) boxplot(V3~gruppe, data=x) Now, I will connect the boxplots to each other to the min, max and median values. Can anybody help me how to do it ? greetings, J -- View this message in context: http://www.nabble.com/connecting-boxplots-tp21405459p21405459.html Sent from

Gracias Carlos. Yo también he visto el ejemplo que te pone chatGPT, pero la salida que te da no soy capaz de interpretarla. Os paso las ordenes y las respuestas de R de la propuesta de chatGPT Ejemplo.aov<- aov(P~TRAT+CORTE+REP) > summary (Ejemplo.aov) Df Sum Sq Mean Sq F value Pr(>F) TRAT 6 0.0028 0.00046 0.777 0.590 CORTE 2 0.5022 0.25110 424.542 <2e-16

Dear Colleagues, In the following simple ggplot2 code: -------------------------------- m <- ggplot(d.fig, aes(time, prob)) m + stat_summary(fun.data = "median_hilow", conf.int = .95, geom = "smooth") + facet_wrap(~ Cohort, nrow=1) + coord_cartesian(ylim = c(0, .03)) -------------------------------- Is there a way to replace the y-axis label from "prob" to

Hello, A few questions about the following examples: 1. Why do the two plotting versions not produce the same result? 2. Is the 'scale_x_continuous' (or *_y_* or *_*_discrete) geom the best way to setup grids (as in visual guide-lines) in polar (or for that matter, any) coordinate system? 3. Why do these commands appear to generate 3 plot pages each? 4. Perhaps more questions to follow

Dear All (probably Hadley), I am now trying to customise some plots using a bar geom. I do not want to use the default binning statistic, but rather calculate the bar heigths separately. I do manage this, but for comparison purposes I would like to have a set of plots all with the same y-axis height. But I do not seem to find out how to fix the scale of the y-axis in this case. Any tips?

I am learning ggplot2 commands specifically qplot for the time being and I have figured out how to create histograms and normal density curves but I am not sure how to add a normal bell curve or other dist. as well 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"),

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

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 want to plot the grouped means of some variables. The dependent variables and the grouping factor are stored in different columns. I want to draw a simple line-plot of means, in which the x-axis represents the variables and y-axis represents the means. The means of the groups should be connected by lines. So far, the only function that I could find comes closest to what I'm

Could someone show me how to get a blue line in this plot? > ggplot(movies, aes(x=rating)) + stat_qq(geom="line", quantiles=seq(0,1,0.005), distribution=qunif) I've tried many permutations but cannot seem to find the right combination. I've tried these flavors: > ggplot(movies, aes(x=rating)) + stat_qq(geom="line", colour="blue",

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