similar to: Histograms without bars

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

I've seen this asked, but never fully answered.  Is it possible to plot stacked histograms in R? I have four data sets that I would like to show combined vertically in histogram format.  Is this possible?  Thank you for any feedback you can provide. P.S. I know I can show the four sets side by side, but I want to combine them, but still uniquely identify each.   Thanks again.

Hi, I wish to plot multiple histograms(representing different data so different range along xaxis but y axis is the same) horizontally in ggplot2. I'd like it to look like facets. Is this possible? -- Rajesh.J [[alternative HTML version deleted]]

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

Suppose that I'm working on Hadley's diamond dataset and I want to review the relationship between price, colour and carat. I might run the following: library(ggplot2) #plot scatter and add some hex binning q<-qplot(carat,price,data=diamonds, geom=c("hex"), main="Variability of Diamond Prices by Carat and Colour") #facet to get one scatter for

Hi all, Is there any way for me to to string in the argument of qplot or ggplot? for example qplot(x='carat',y='price',data=diamonds,geom=c('point','smooth')) instead of qplot(x=carat,y=price,data=diamonds,geom=c('point','smooth')) Thanks!! Regards, TszKin Julian [[alternative HTML version deleted]]

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 With ggplot2 I can very easily create beautiful histograms but I would like to put two histograms on the same plot. The histograms may be over-lapping. When they are overlapping the bars are shown on top of each other (so that the overall height is the sum of the two). Is there any way to get them to display overlapping (with smaller value in front, larger value behind) so that the overall

Hello I need to plot a histogram, but insted of using bars, I'd like to plot the data points. I've been doing it like this so far: h <- hist(x, plot = F) plot(y = x$counts / sum(x$counts), x = x$breaks[2:length(x$breaks)], type = "p", log = "xy") Sometimes I want to have a look at the "raw" data (avoiding any kind of binning). When x

Hi, I'm using the gridExtra package to combine some graphs like in the arrangeGrob example. Each of the graphs has a title but they appear much larger than the overall combined plot title and left axis label. Does anyone know how I can control the style / size of the gridExtra labels? library(gridExtra) library(ggplot2) dsamp <- diamonds[sample(nrow(diamonds), 1000), ] p1 <-

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

I am interested in creating a boxplot using ggplot or qplot where I can specify the order of the categories being plotted on the x-axis. For example, the following command plots the categories (diamond color) in alphabetic order (D, E, ..., J): qplot(color, price/carat, data=diamonds, geom="boxplot") I want to know how I can modify this command so that the categories are plotted in a

Hi, Does anyone know how to do a coord_trans() in which the y-axis is tranformed into (for example) -1000/y? Thanks, _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box 400400 Charlottesville, VA 22904-4400 Parcels: Room 102 Gilmer Hall McCormick Road Charlottesville, VA 22903 Office: B011

Hi Ian, Per your suggestion, I reinstalled R 2.9.0, then I reinstalled ggplot2 on top. The problem persists. Here's the what happens after the installation: > qplot (carat, price, data = diamonds, alpha = I(1/10)) Warning message: In grid.Call.graphics("L_points", x$x, x$y, x$pch, x$size) : semi-transparency is not supported on this device: reported only once per

I have some data where the frequency is heavily weighted on the lower end. So I have lots of low values with very few higher values. I would like to find breakpoints that cover the data with as much detail as possible. I find that if I use hist() to automatically find the breaks for me it finds breaks that are too coarse for the low values. I have tried the other algorithms (like 'Scott'

I can plot to png's fine when i run this directly from the top-level script/console: png('diamonds.png');qplot(carat,price,data=diamonds);dev.off() But for some reason it's not working when that's in a function: (function(){png('diamonds.png');qplot(carat,price,data=diamonds);dev.off()})() I suspect this is because the qplot's return value must be

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 Hadley: I'm practicing writing a document using MikTex but can't make qplot to execute. It works when using 'plot' though. Is this a normal behaviour? \documentclass[9pt]{article} \title{ggplot2 example} \begin{document} \maketitle \section*{Examples of using ggplot2} The goal is to be able to import ggplot2 graphics into the annual report. Hadley Wickham has done a great

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

My question is related to plot( ) in the mgcv package. Before modelling the data, a few predictors were transformed to normalize them. Therefore, the x-axes in the plots show transformed predictor values. How do I back-transform the predictors so that the plots are easier to interpret? Thanks in advance, Suzan -- Suzan Pool Oregon State University Cooperative Institute for Marine