Error Bars R Barplot
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R Bar Plot With Error Bars
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Barplot With Error Bars Ggplot2
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Barplot With Error Bars Matlab
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Biodemography → Plotting Error Bars in R August 24th, 2009 · 52 Comments · R One common frustration that I have heard errbar r expressed about R is that there is no automatic way to plot error bars (whiskers really) on bar plots. I just encountered this issue revising a paper for submission and figured I'd share my code. https://www.r-bloggers.com/bar-plot-with-error-bars-in-r/ The following simple function will plot reasonable error bars on a bar plot. PLAIN TEXT R: error.bar <- function(x, y, upper, lower=upper, length=0.1,...){ if(length(x) != length(y) | length(y) !=length(lower) | length(lower) != length(upper)) stop("vectors must be same length") arrows(x,y+upper, x, y-lower, angle=90, code=3, length=length, ...) } Now let's use it. First, I'll create 5 means drawn from a Gaussian random variable with unit mean and variance. I want to point http://monkeysuncle.stanford.edu/?p=485 out another mild annoyance with the way that R handles bar plots, and how to fix it. By default, barplot() suppresses the X-axis. Not sure why. If you want the axis to show up with the same line style as the Y-axis, include the argument axis.lty=1, as below. By creating an object to hold your bar plot, you capture the midpoints of the bars along the abscissa that can later be used to plot the error bars. PLAIN TEXT R: y <- rnorm(500, mean=1) y <- matrix(y,100,5) y.means <- apply(y,2,mean) y.sd <- apply(y,2,sd) barx <- barplot(y.means, names.arg=1:5,ylim=c(0,1.5), col="blue", axis.lty=1, xlab="Replicates", ylab="Value (arbitrary units)") error.bar(barx,y.means, 1.96*y.sd/10) Now let's say we want to create the very common plot in reporting the results of scientific experiments: adjacent bars representing the treatment and the control with 95% confidence intervals on the estimates of the means. The trick here is to create a 2 x n matrix of your bar values, where each row holds the values to be compared (e.g., treatment vs. control, male vs. female, etc.). Let's look at our same Gaussian means but now compare them to a Gaussian r.v. with mean 1.1 and unit variance. PLAIN TEXT R: y1 <- rnorm(500, mean=1.1) y1 <- matrix(y1,100,5) y1.means <- apply(y1,2,mean) y1.sd <- a
here for a quick overview of the site Help Center Detailed answers to any questions you might have Meta Discuss the workings and policies of this site About Us Learn more about Stack http://stackoverflow.com/questions/29995480/side-by-side-r-barplot-with-error-bars Overflow the company Business Learn more about hiring developers or posting ads with us Stack Overflow Questions Jobs Documentation Tags Users Badges Ask Question x Dismiss Join the Stack Overflow Community Stack Overflow is a http://blog.revolutionanalytics.com/2009/09/making-barplots-with-error-bars-in-r.html community of 4.7 million programmers, just like you, helping each other. Join them; it only takes a minute: Sign up Side by Side R Barplot with error bars up vote 0 down vote favorite say I error bars have the means of two datasets that I want to plot as barplots with error bars next to each other in ggplot2, or base Each dataset consists of a matrix of numbers 10 20 12 10 20 12 10 20 12 which is then transformed into a mean vector of for example 3 elements 10 20 12 What I want to do is to take both mean vectors and plot them plot with error as a bar plot where the first element of one is besides the first element of the other Dataset1Element1Bar-Dataset2Element1Bar Dataset1Element2Bar-Dataset2Element2Bar etc Give each bar an error bar, say of standard deviation. I know I can calculate it through sd but I'm not sure how to stick it into the graph in the proper form And lastly color them by their element number (ie Element 1) I have the code to do one dataset but I'm not sure where to go from there. result<-barplot(bardata, main="Mean Coverage", names.arg=namePosTargetGroup, ylab="mean Magnitude", cex.names=.4,col=c("red","blue","green")) legend(10,legend=c("Group1","Group2","Group3"),fill = c("red","blue","green")) A lot of what I look up gives the answer for one thing or another but its difficult to figure out how to combine them together. r graph plot ggplot2 share|improve this question asked May 1 '15 at 21:33 A D 428 add a comment| 1 Answer 1 active oldest votes up vote 1 down vote I would generally not recommend plotting just a bar chart with error bars. There are many other ways to plot your data, which reveal the data and its structure a lot better. Especially if you just have very few cases, plotting means with bars is not good. A good explanation can be found here: Beyond Bar and Line Graphs: Time for a Ne
11, 2009 Making barplots with error bars in R When presenting summarized data -- the data in the cells of a two-way ANOVA, for example -- it's always a good idea to visualize the uncertainty in the summaries. The natural way for statisticians is to use a boxplot, and ggplot2 makes that easy: qplot(class, hwy, fill=factor(year), data=mpg, geom="boxplot", position="dodge")+theme_bw() But Jarrett Byrnes, a marine community biologist, wanted to use a barplot, instead. (A boxplot shows more details of the distribution, but more people know how to read a barplot.) As he shows, it is possible, with a little extra work, add error bars to a barplot with ggplot2: See the link below for the code: a great demonstration of the customization capabilities of ggplot2. i’m a chordata! urochordata!: Let’s All Go Down to the Barplot! (Update Jan 2 2013: link to http://www.imachordata.com/?p=199 removed -- site compromised) Posted by David Smith at 07:11 in graphics, R | Permalink Comments You can follow this conversation by subscribing to the comment feed for this post. The comments to this entry are closed. Information About this blog Comments Policy About Categories About the Authors Local R User Group Directory Tips on Starting an R User Group Search Revolutions Blog Got comments or suggestions for the blog editor? Email David Smith. Follow David on Twitter: @revodavid +David Smith Get this blog via email with Categories academia advanced tips announcements applications beginner tips big data courses current events data science developer tips events finance government graphics high-performance computing life sciences Microsoft open source other industry packages popularity predictive analytics profiles python R R is Hot random reviews Revolution Rmedia roundups sports statistics user groups See More R links Find R packagesCRAN package directory at MRAN Download Microsoft R OpenFree, high-performance R R Project siteInformation about the R project Recommended Sites FlowingDataModern data visualization One R Tip A DayCode examples for graphics and analysis Probability and statistics blogMonte Carlo simulations in R R BloggersDaily news and tutorials about R, contributed by R bloggers worldwide. R Project group on analyticbridge.comCommunity and discussion forum Statistical Modeling, Causal Inference, and Social ScienceAndrew Gelman's statistics blog Archives October 2016 September 2016 August 2016 July 2016 June 2016 May 2016 April 2016 March 2016 February 2016 January 2016 Subscribe to this blog's feed