# Ggplot2 Bar Graph With Error Bars

error bars Two within-subjects variables Note about normed means Helper functions Problem

## R Calculate Standard Error

You want to plot means and error bars for ggplot2 stat_summary a dataset. Solution To make graphs with ggplot2, the data must be in a summaryse data frame, and in “long” (as opposed to wide) format. If your data needs to be restructured, see this page for more information.

## Barplot With Error Bars R

Sample data 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)

## Error Bars In R

#> len supp 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",<

Installing R/RStudio Running R/RStudio R Programming Basics Getting Help Installing R Packages R Built-in data sets Importing Data Preparing ggplot confidence interval Files Importing txt|csv: R Base Functions Fast Importing txt|csv: readr package

## Error.bar Function R

Importing Excel Files Exporting Data Exporting to txt|csv Files: R Base Functions Fast Exporting to txt|csv Files: geom_errorbar linetype readr package Exporting to Excel Files Saving Data into RDATA and RDS Formats Word Document Word Document from Template Add Table into Word Document Powerpoint Document Editable http://cookbook-r.com/Graphs/Plotting_means_and_error_bars_(ggplot2)/ Graph From R to Powerpoint Reshaping Data Data Manipulation Data Visualization R Base Graphs Lattice Graphs Ggplot2 3D Graphics How to Choose Great Colors? Basic Statistics Descriptive Statistics and Graphics Normality Test in R Statistical Tests and Assumptions Correlation Analysis Correlation Test Between Two Variables in R Correlation Matrix: Analyze, Format & Visualize Visualize http://www.sthda.com/english/wiki/ggplot2-error-bars-quick-start-guide-r-software-and-data-visualization Correlation Matrix using Correlogram Elegant Correlation Table using xtable R Package Correlation Matrix : An R Function to Do All You Need Comparing Means One-Sample vs Standard Known Mean One-Sample T-test (parametric) One-Sample Wilcoxon Test (non-parametric) Two Independent Groups Unpaired Two Samples T-test (parametric) Unpaired Two-Samples Wilcoxon Test (non-parametric) Paired Samples Paired Samples T-test (parametric) Paired Samples Wilcoxon Test (non-parametric) More Than Two Groups One-Way ANOVA Test in R Two-Way ANOVA Test in R MANOVA: Multivariate ANOVA Kruskal-Wallis (non-parametric) Comparing Variances F-Test: Compare Two Variances Compare Multiple Sample Variances Comparing Proportions One-Proportion Z-Test Two-Proportions Z-Test Chi-Square Goodness of Fit Test Chi-Square Test of Independence Cluster Analysis Overview Distance Measures Basic Clustering Partitionning Methods Hierarchical Clustering Clustering Evaluation & Validation Clustering Tendency Optimal Number of Clusters Validation Statistics Compare Clustering Algorithms p-value for Hierarchical Clustering Quick Guide for Cluster Analysis Clustering Visualization Visual Enhancement of Clustering Beautiful Dendrograms Static and Interactive Heatmap Advanced Clustering Fuzzy Clustering Model-Based Clustering Density-Based Clustering Hybrid Hierarchical Kmea

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 http://stackoverflow.com/questions/15064462/r-ggplot2-barplot-and-error-bar 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 community https://www.youtube.com/watch?v=N4d-qUTTY44 of 4.7 million programmers, just like you, helping each other. Join them; it only takes a minute: Sign up R: ggplot2 barplot and error bar up vote 2 down vote favorite Since the new version of error bars ggplot2 (0.9.3), I've problem to plot barplots with errorbars. So I've a dataframe like this : group N val sd se ci 1 206 3 37.2269533 7.9688645 4.6008261 19.7957568 2 207 3 2.0731505 2.2843009 1.3188417 5.6745180 3 208 3 2.2965978 1.4120606 0.8152536 3.5077531 4 209 3 3.1085132 1.1986664 0.6920504 2.9776525 5 210 3 3.3735251 1.9226134 1.1100214 4.7760365 6 211 3 4.0477951 2.9410503 1.6980162 7.3059739 7 212 3 1.2391158 1.2345554 0.7127709 3.0668055 8 with error bars 213 2 1.3082374 1.1234220 0.7943793 10.0935460 I want to plot for each group the val +- s : I did that before upgrade : ggplot(dfc, aes(x=factor(group), y=factor(val)) + geom_bar(position=position_dodge()) + geom_errorbar(aes(ymin=val-se, ymax=val+se),width=.1,position=position_dodge(.9)) It gives me that: 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) So anyone knows how to resolve that ? Thanks N. r ggplot2 share|improve this question asked Feb 25 '13 at 10:06 NicoBxl 3374515 add a comment| 1 Answer 1 active oldest votes up vote 6 down vote accepted Is this what you're after? my.df <- read.table(text = "group N val sd se ci 206 3 37.2269533 7.9688645 4.6008261 19.7957568 207 3 2.0731505 2.2843009 1.3188417 5.6745180 208 3 2.2965978 1.4120606 0.8152536 3.5077531 209 3 3.1085132 1.1986664 0.6920504 2.9776525 210 3 3.3735251 1.9226134 1.1100214 4.7760365 211 3 4.0477951 2.9410503 1.6980162 7.3059739 212 3 1.2391158 1.

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