similar to: ggplot2: scale_y_log10() with geom_histogram

Hi, I have a histogram.But I need seperate colours for fixed range of values.for eg. between 2-3 on the x axis a colour.3-4 another colour etc. and the legend has to say what each colour is.How can this be done in geom_histogram? -- Rajesh.J [[alternative HTML version deleted]]

Dear All, I would like to be able to plot histograms/densities on a semi-log or log-log scale. I found several suggestions online http://tolstoy.newcastle.edu.au/R/help/05/09/12044.html https://stat.ethz.ch/pipermail/r-help/2002-June/022295.html http://www.harding.edu/fmccown/R/#histograms Now, consider the code snippet taken from http://www.harding.edu/fmccown/R/#histograms # Get a random

Hello, I have written a function that demonstrates the CLT by generating samples following the exponential distribution, calculating the means, plotting the histogram, and drawing the limiting normal curve as an overlay. I have the title of each histogram state the sample size and rate (1/theta) for the exponential (the output is actually 4 histograms), but I can't get the greek letter theta

Hello all. I'm just a beginner trying to draw a boxplot and I don't know why every time I try to make it horizontal I receive the error message "parameter 'horizontal' couldn't be set in high-level plot() function". Can anybody give me an advice? Here is the code: opar <- par(ask = interactive() && (.Device == "X11" || .Device ==

Hi everyone, I've run into a bit of strange problem with implicit vs explicit printing and the call stack. I've included an example at the bottom of this email. The basic problem is that I have an S3 object with a print method. When the object is implicitly printed (ie. typed directly into the console) the function arguments in the call stack are exploded out to their actual values,

I have a function: myplot <- function (X) { d <- plotCounts(dds2, gene=X, intgroup="condition", returnData=TRUE) png(paste("img/", X, ".png", sep="")) ggplot(d, aes(x=condition, y=count, color=condition)) + geom_point(position=position_jitter(w=0.1,h=0)) + scale_y_log10(breaks=c(25,100,400)) + ggtitle(X) +

Hi: Does anyone have an idea on how to color the axis and labels using ggplot2? This is what I got: library(ggplot2) p <- qplot(total_bill, tip, data = tips) NewPlot<- p + geom_abline(slope=c(0.1,0.15,0.2), colour=c("red","blue","yellow"),size=c(2,5,2)) NewPlot + geom_smooth(colour="green", size=3,linetype=3)

I don't really understand. I mean, I understand the solution is print(ggplot(...)). But why is that required in a function and not at the console? Shouldn't I be able to rely on what I do at the console working in a script? Is this inconsistent behavior by design? On Thu, Nov 2, 2017 at 11:54 AM, David Winsemius <dwinsemius at comcast.net> wrote: > >> On Nov 2, 2017,

> On Nov 2, 2017, at 9:27 AM, Ed Siefker <ebs15242 at gmail.com> wrote: > > I have a function: > > myplot <- function (X) { > d <- plotCounts(dds2, gene=X, intgroup="condition", returnData=TRUE) > png(paste("img/", X, ".png", sep="")) > ggplot(d, aes(x=condition, y=count, color=condition)) + >

Full_Name: Daniel Egloff Version: 1.2.1 OS: Linux Redhat 7.0 Submission from: (NULL) (212.35.34.200) Externals in the shared library libc.so.6 not found. See the following R session, with the abort message at the end. > demo(graphics) demo(graphics) ---- ~~~~~~~~ Type <Return> to start : > opar <- par(ask = interactive() && (.Device %in%

Say I have a dataset that looks like Location Year GW_Elv MW01 1999 546.63 MW02 1999 474.21 MW03 1999 471.94 MW04 1999 466.80 MW01 2000 545.90 MW02 2000 546.10 The whole dataset is at http://doylesdartden.com/ExampleData.csv and I use the code below to do the graph but I want to do it without MW01. How can I

I'm learning ggplot and am a little confused. Sometimes discrete scales work like I'd expect, and sometimes they don't. For example... This works exactly like one would expect: df<-data.frame(names=c("Bob","Mary","Joe","Bob","Bob")) ggplot(df,aes(names))+geom_histogram() But this yields an error:

Dear R users, I was wondering from where I could get the C source code to compute pnbinom() and qnorm() ? (I would use R in batch mode but I find the startup time prohibitive, unless there is a way to speed it up) I searched the Web and it clearly is part of the R distribution, I just don't know how to extract them. Thanking you ! Markus Loecher Princeton, NJ [[alternative HTML version

This is a solution I am posting for a problem that others may have. If you want to: 1. Place lattice graphics from R into an Adobe InDesign document, and 2. Use the export as eps function in R to maximize resolution (it is much better than exporting as a metafile or bitmap), and 3. Use long strings of text in your titles or captions or to label your axes. Then you will have problems because:

Hello - I am trying to plot flows in a number of rivers within the same plot, and need to colour the lines differently, using a colour-blind palette. Code beneath works but has colours assigned by the program I have made some simple dummy data: ## code 1 cb8<- c("#000000", "#E69F00", "#56B4E9", "#009E73","#F0E442", "#0072B2",

Hi, When I zoom into a graph created in ggplot2 with the coord_cartesian(ylim=c(0,5)) option, I have no values labelled on my y-axis. For this graph ggplot2 only puts labels the y-axis at intervals of 10 (i.e. 0, 10, 20, ...). However, the major portion of the graph I am interested in is located between the values of 0 and 5 on the y-axis (thus why I am zoooming). How can I coerce ggplot2 into

Dear R gurus, I want to wrap labels that are too long for a plot. I have looked at strsplit(), substr(), nchar(), and strwrap(). I think it's some combination but I'm having difficulty trying to figure out the right combo. I think I need to create some new matrix containing the labels already split, though I'm not sure if maybe there is a quick and dirty way to address this

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

Dear R users, I have been diligently using the apply() family in order to avoid explicit for loops and speed up computation. However, when I finally inspected the source code for apply, it appears that the core computation is a simple loop as well. What am I missing ? Why the often found advice to use apply() instead of loops and the actually observed empirical speedups on many tasks ? Thanks in

The MASS package is listed on the CRAN web site ( http://cran.r-project.org/web/packages/MASS/index.html) but I am unable to install it via install.packages(). The error is that the package is "unavailable". When I manually download the source tar ball and try to install it on a Linux machine, installation fails because "it is not a valid package". Do I need to search