Error Bar Plot R
Contents |
by over 573 bloggers. There are many ways to follow us - By e-mail: On Facebook: If you are an R error.bar function r blogger yourself you are invited to add your own R content feed to error bar plot matlab this site (Non-English R bloggers should add themselves- here) Jobs for R-usersFinance Manager @ Seattle, U.S.Data Scientist – AnalyticsTransportation error bar plot in excel 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 to import image file to
Error Bar Plot Sas
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 (Part 3) Danger, Caution H2O steam is error bar plot mathematica 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$gear), FUN = function(x) c(mean = mean(x), sd = sd(x), n = length(x))) After this, we'll nee
here for a quick overview of the site Help Center Detailed answers to any questions you might have Meta Discuss the workings and policies of this site About Us Learn more about error bar plot python Stack Overflow the company Business Learn more about hiring developers or posting ads with
Error Bars In R Barplot
us Stack Overflow Questions Jobs Documentation Tags Users Badges Ask Question x Dismiss Join the Stack Overflow Community Stack Overflow is
Errbar R
a community of 4.7 million programmers, just like you, helping each other. Join them; it only takes a minute: Sign up Add error bars to show standard deviation on a plot in R up vote https://www.r-bloggers.com/building-barplots-with-error-bars/ 23 down vote favorite 10 For each X-value I calculated the average Y-value and the standard deviation (sd) of each Y-value x = 1:5 y = c(1.1, 1.5, 2.9, 3.8, 5.2) sd = c(0.1, 0.3, 0.2, 0.2, 0.4) plot (x, y) How can I use the standard deviation to add error bars to each datapoint of my plot? r plot statistics standard-deviation share|improve this question edited Oct 16 '14 at 3:43 http://stackoverflow.com/questions/15063287/add-error-bars-to-show-standard-deviation-on-a-plot-in-r Craig Finch 11417 asked Feb 25 '13 at 8:59 John Garreth 4572413 also see plotrix::plotCI –Ben Bolker Feb 25 '13 at 15:13 add a comment| 5 Answers 5 active oldest votes up vote 16 down vote accepted A Problem with csgillespie solution appears, when You have an logarithmic X axis. The you will have a different length of the small bars on the right an the left side (the epsilon follows the x-values). You should better use the errbar function from the Hmisc package: d = data.frame( x = c(1:5) , y = c(1.1, 1.5, 2.9, 3.8, 5.2) , sd = c(0.2, 0.3, 0.2, 0.0, 0.4) ) ##install.packages("Hmisc", dependencies=T) library("Hmisc") # add error bars (without adjusting yrange) plot(d$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 24.1k56081 add a comment| up vote 18 down vote
|| is.character(x)) "" else as.character(substitute(y)), add=FALSE, lty=1, type='p', ylim=NULL, lwd=1, pch=16, Type=rep(1, length(y)), ...) Arguments x vector of numeric x-axis values (for vertical error bars) or a factor or character variable (for horizontal error http://svitsrv25.epfl.ch/R-doc/library/Hmisc/html/errbar.html bars, x representing the group labels) y vector of y-axis values. yplus vector of y-axis values: the tops of the error bars. yminus vector of y-axis values: the bottoms of the error bars. cap http://rstatistics.tumblr.com/post/470327991/make-a-barplot-with-errorbars-now-this-is-a the width of the little lines at the tops and bottoms of the error bars in units of the width of the plot. Defaults to 0.015. main a main title for the plot, error bar see also title. sub a sub title for the plot. xlab optional x-axis labels if add=FALSE. ylab optional y-axis labels if add=FALSE. Defaults to blank for horizontal charts. add set to TRUE to add bars to an existing plot (available only for vertical error bars) lty type of line for error bars type type of point. Use type="b" to connect dots. ylim y-axis limits. Default is to error bar plot use range of y, yminus, and yplus. For horizonal charts, ylim is really the x-axis range, excluding differences. lwd line width for line segments (not main line) pch character to use as the point. Type used for horizontal bars only. Is an integer vector with values 1 if corresponding values represent simple estimates, 2 if they represent differences. ... other parameters passed to all graphics functions. Details errbar adds vertical error bars to an existing plot or makes a new plot with error bars. It can also make a horizontal error bar plot that shows error bars for group differences as well as bars for groups. For the latter type of plot, the lower x-axis scale corresponds to group estimates and the upper scale corresponds to differences. The spacings of the two scales are identical but the scale for differences has its origin shifted so that zero may be included. If at least one of the confidence intervals includes zero, a vertical dotted reference line at zero is drawn. Author(s) Charles Geyer, University of Chicago. Modified by Frank Harrell, Vanderbilt University, to handle missing data, to add the parameters add and lty, and to implement horizontal charts with differences. Examples set.seed(1) x
a barplot with errorbars Now this is a tricky one: I wrote a script to plot a barplot with errorbars. I used the following script: #barplot where x is the independent on the x-axis, y is the #dependent on the y-axis and z is the independent given by #different colored bars anova.plot<-function(x, y, z, ylab="y", xlab="x", ylim=c(0, max(xx)+max(yy)), length=0.05){ #height of the bars xx<-tapply(y,list(z,x),mean) #standard deviation yy<-tapply(y,list(z,x),sd) #number of replicates zz<-tapply(y,list(z,x),length) #standard error er<-yy/sqrt(zz) #number of colors for bars w<-length(levels(z)) #simple barplot without the errorbars barx<-barplot(xx, col=c(1:w), beside=T, ylab=ylab, xlab=xlab, ylim=ylim,xpd=FALSE) #box around the plot box() #error bars arrows(barx,xx+er, barx, xx, angle=90, code=1, length=length) #legend (after making the plot, indicate where the legend has #to come with the mouse) legend(locator(1),c(levels(z)),fill=c(1:w),bty="n",cex=0.8) } If you have set your palette to: palette(c("grey25","grey50","grey75","white")) you get a plot like the one above if you use: anova.plot(x,y,z) (6 years ago) archive : rss : theme "2001" by 54mf : powered by Tumblr