R Plot Error Bars
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Error.bar Function R
Stack Overflow Community Stack Overflow is a community of 6.2 million programmers, just like you, helping each other. Join them; it only takes a minute: error bars in r barplot Sign up Add error bars to show standard deviation on a plot in R up vote 23 down vote favorite 10 For each X-value I calculated the average Y-value and the standard deviation (sd) of each Y-value x = 1:5 y
Errbar R
= c(1.1, 1.5, 2.9, 3.8, 5.2) sd = c(0.1, 0.3, 0.2, 0.2, 0.4) plot (x, y) How can I use the standard deviation to add error bars to each datapoint of my plot? r plot statistics standard-deviation share|improve this question edited Oct 16 '14 at 3:43 Craig Finch 11417 asked Feb 25 '13 at 8:59 John Garreth 4572413 also see plotrix::plotCI –Ben Bolker Feb 25 '13 at 15:13 add a comment| 5 Answers 5 active oldest votes up vote 16 down r summaryse vote accepted A Problem with csgillespie solution appears, when You have an logarithmic X axis. The you will have a different length of the small bars on the right an the left side (the epsilon follows the x-values). You should better use the errbar function from the Hmisc package: d = data.frame( x = c(1:5) , y = c(1.1, 1.5, 2.9, 3.8, 5.2) , sd = c(0.2, 0.3, 0.2, 0.0, 0.4) ) ##install.packages("Hmisc", dependencies=T) library("Hmisc") # add error bars (without adjusting yrange) plot(d$x, d$y, type="n") with ( data = d , expr = errbar(x, y, y+sd, y-sd, add=T, pch=1, cap=.1) ) # new plot (adjusts Yrange automatically) with ( data = d , expr = errbar(x, y, y+sd, y-sd, add=F, pch=1, cap=.015, log="x") ) share|improve this answer answered Sep 6 '13 at 14:21 R_User 3,20984683 add a comment| up vote 19 down vote A solution with ggplot2 : qplot(x,y)+geom_errorbar(aes(x=x, ymin=y-sd, ymax=y+sd), width=0.25) share|improve this answer answered Feb 25 '13 at 9:06 juba 24.3k56081 add a comment| up vote 18 down vote You can use segments to add the bars in base graphics. Here epsilon controls the line across the top and bottom of the line. plot (x, y, ylim=c(0, 6)) epsilon = 0.02 for(i in 1:5) { up = y[i] + sd[i] low = y[i] - sd[i] segments(x[i],low , x[i], up) segments(x[i]-epsilon, up , x[i]+epsilon, up) segments(x[i]-epsilon, low , x[i]+epsilon, low) } As @thelatemail points out, I should really have used vectorised function calls: segments(x, y-sd,x, y+sd
error bars Two within-subjects variables Note about normed means Helper functions Problem You want
R Arrows
to plot means and error bars for a dataset.
Ggplot2 Error Bars
Solution To make graphs with ggplot2, the data must be in a data frame, plot mean and standard deviation in r and in “long” (as opposed to wide) format. If your data needs to be restructured, see this page for more information. Sample data http://stackoverflow.com/questions/15063287/add-error-bars-to-show-standard-deviation-on-a-plot-in-r The examples below will the ToothGrowth dataset. Note that dose is a numeric column here; in some situations it may be useful to convert it to a factor. tg <- ToothGrowth head(tg) #> len supp http://cookbook-r.com/Graphs/Plotting_means_and_error_bars_(ggplot2)/ dose #> 1 4.2 VC 0.5 #> 2 11.5 VC 0.5 #> 3 7.3 VC 0.5 #> 4 5.8 VC 0.5 #> 5 6.4 VC 0.5 #> 6 10.0 VC 0.5 library(ggplot2) First, it is necessary to summarize the data. This can be done in a number of ways, as described on this page. In this case, we’ll use the summarySE() function defined on that page, and also at the bottom of this page. (The code for the summarySE function must be entered before it is called here). # summarySE provides the standard deviation, standard error of the mean, and a (default 95%) confidence interval tgc <- summarySE(tg, measurevar="len", groupvars=c( by over 573 bloggers. There are many ways to follow us - By e-mail: On Facebook: If you are an R blogger yourself you are invited to add your own R content https://www.r-bloggers.com/building-barplots-with-error-bars/ feed to this site (Non-English R bloggers should add themselves- here) Jobs for R-usersStatistical Analyst https://plot.ly/r/error-bars/ @ Rostock, Mecklenburg-Vorpommern, GermanyData EngineerData Scientist – Post-Graduate Programme @ Nottingham, EnglandDirector, Real World Informatics & Analytics Data Science @ Northbrook, Illinois, U.S.Junior statistician/demographer for UNICEF Popular Searches web scraping heatmap twitter maps time series animation boxplot shiny hadoop ggplot2 how to import image file to R trading finance latex eclipse rstudio excel SQL ggplot quantmod knitr googlevis PCA market error bars research rattle regression map tutorial coplot rcmdr Recent Posts Election 2016: Tracking Emotions with R and Python Data science for executives and managers The Worlds Economic Data, Shiny Apps and all you want to know about Propensity Score Matching! August Package Picks Slack all the things! Warsaw R-Ladies Notes from the Kölner R meeting, 14 October 2016 anytime 0.0.4: New features and fixes 2016-13 ‘DOM’ Version 0.3 Building a package automatically The new R Graph error bars in Gallery Network Analysis Part 3 Exercises Annotated Facets with ggplot2 Paper published: mlr - Machine Learning in R a grim knight [cont’d] Other sites Jobs for R-users SAS blogs Building Barplots with Error Bars August 17, 2015By Chris Wetherill (This article was first published on DataScience+, and kindly contributed to R-bloggers) Bar charts are a pretty common way to represent data visually, but constructing them isn't always the most intuitive thing in the world. One way that we can construct these graphs is using R's default packages. Barplots using base R Let's start by viewing our dataframe: here we will be finding the mean miles per gallon by number of cylinders and number of gears. View(mtcars) We begin by aggregating our data by cylinders and gears and specify that we want to return the mean, standard deviation, and number of observations for each group: myData <- aggregate(mtcars$mpg, by = list(cyl = mtcars$cyl, gears = mtcars$gear), FUN = function(x) c(mean = mean(x), sd = sd(x), n = length(x))) After this, we'll need to do a little manipulation since the previous function returned matrices instead of vectors myData <- do.call(data.frame, myData) And now let's compute the standard error for each group. We can then rename the columns just for ease of use. myData$se <- myData$x.sd / sqrt(myData$x.n) colnames(myData) <- c("cyl", "gears", "mean", "sd", "n", "se") myData$names instant chat support from our awesome engineering team. plotly Pricing PLOTCON NYC API Sign In SIGN UP + NEW PROJECT UPGRADE REQUEST DEMO Feed Pricing Make a Chart API Sign In SIGN UP + NEW PROJECT UPGRADE REQUEST DEMO Show Sidebar Hide Sidebar Help API Libraries R Error Bars Fork on Github Navigation Back to R Error Bars in R How to add error bars to scatter plots in R. R matplotlib Python plotly.js Pandas node.js MATLAB Error Bars library(dplyr) ## Warning: package 'dplyr' was built under R version 3.2.5 library(plotly) ## Warning: package 'ggplot2' was built under R version 3.2.4 data <- mpg %>% group_by(class) %>% summarise(highway = mean(hwy), sd = 1.96 * sd(hwy), city = mean(cty)) %>% arrange(desc(highway)) %>% tidyr::gather(key