Drawing Error Bars In R
Contents |
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 Overflow the company Business Learn more about hiring
Scatter Plot With Error Bars In R
developers or posting ads with us Stack Overflow Questions Jobs Documentation Tags Users Badges Ask error bars in r barplot Question x Dismiss Join the Stack Overflow Community Stack Overflow is a community of 4.7 million programmers, just like you, helping each other. Join
Error.bar Function R
them; it only takes a minute: 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 errbar r (sd) of each Y-value x = 1:5 y = 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 r summaryse a comment| 5 Answers 5 active oldest votes up vote 16 down 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 3,18984581 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 24k56081 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) segme
error bars Two within-subjects variables Note about normed means Helper functions Problem You want
R Plot Standard Deviation
to plot means and error bars for a dataset. r arrows Solution To make graphs with ggplot2, the data must be in a data frame,
R Ggplot Error Bars
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("supp", by over 573 bloggers. There are many ways to follow us - By e-mail: On Facebook: If you are https://www.r-bloggers.com/building-barplots-with-error-bars/ an R blogger yourself you are invited to add your own R content feed to this site (Non-English R bloggers should add themselves- here) Jobs for R-usersFinance Manager @ Seattle, U.S.Data http://docs.ggplot2.org/0.9.3.1/geom_errorbar.html Scientist – AnalyticsTransportation Market Research Analyst @ Arlington, U.S.Data AnalystData Scientist for Madlan @ Tel Aviv, Israel Popular Searches web scraping heatmap twitter maps time series boxplot animation shiny how error bars to import image file to R hadoop Ggplot2 trading latex finance eclipse excel quantmod sql googlevis PCA knitr rstudio ggplot market research rattle regression coplot map tutorial rcmdr Recent Posts RcppAnnoy 0.0.8 R code to accompany Real-World Machine Learning (Chapter 2) R Course Finder update ggplot2 2.2.0 coming soon! All the R Ladies One Way Analysis of Variance Exercises GoodReads: Machine Learning error bars in (Part 3) Danger, Caution H2O steam is very hot!! R+H2O for marketing campaign modeling Watch: Highlights of the Microsoft Data Science Summit A simple workflow for deep learning gcbd 0.2.6 RcppCNPy 0.2.6 Using R to detect fraud at 1 million transactions per second Introducing the eRum 2016 sponsors 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 = funct needs to be set at the layer level if you are overriding the plot defaults. data A layer specific dataset - only needed if you want to override the plot defaults. stat The statistical transformation to use on the data for this layer. position The position adjustment to use for overlappling points on this layer ... other arguments passed on to layer. This can include aesthetics whose values you want to set, not map. See layer for more details. Description Error bars. Aesthetics geom_errorbar understands the following aesthetics (required aesthetics are in bold): x ymax ymin alpha colour linetype size width Examples # Create a simple example dataset df # Because the bars and errorbars have different widths # we need to specify how wide the objects we are dodging are dodge Mapping a variable to y and also using stat="bin". With stat="bin", it will attempt to set the y value to the count of cases in each group. This can result in unexpected behavior and will not be allowed in a future version of ggplot2. If you want y to represent counts of cases, use stat="bin" and don't map a variable to y. If you want y to represent values in the data, use stat="identity". See ?geom_bar for examples. (Deprecated; last used in version 0.9.2) p Mapping a variable to y and also using stat="bin". With stat="bin", it will attempt to set the y value to the count of cases in each group. This can result in unexpected behavior and will not be allowed in a future version of ggplot2. If you want y to represent counts of cases, use stat="bin" and don't map a variable to y. If you want y to represent values in the data, use stat="identity". See ?geom_bar for examples. (Deprecated; last used in version 0.9.2) p + geom_bar(position=dodge) + geom_errorbar(limits, position=dodge, width=0.25) Mapping a variable to y and also using stat="bin". With stat="bin", it will attempt to set the y value to the cou