R Error Bars Ggplot
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needs to be set at the layer level if you are overriding the plot defaults. data A layer specific dataset - only needed if summaryse r you want to override the plot defaults. stat The statistical transformation
R Calculate Standard Error
to use on the data for this layer. position The position adjustment to use for overlappling ggplot2 stat_summary 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 ggplot confidence interval 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
Barplot With Error Bars R
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 u
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Error.bar Function R
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Tour Start here for a quick overview of the site Help Center Detailed answers to any http://stats.stackexchange.com/questions/14147/calculating-standard-error-and-attaching-an-error-bar-on-ggplot2-bar-chart questions you might have Meta Discuss the workings and policies of http://stackoverflow.com/questions/32842923/specify-error-bars-with-ggplot-and-facet-grid this site About Us Learn more about Stack Overflow the company Business Learn more about hiring developers or posting ads with us Cross Validated Questions Tags Users Badges Unanswered Ask Question _ Cross Validated is a question and answer site for people error bars interested in statistics, machine learning, data analysis, data mining, and data visualization. Join them; it only takes a minute: Sign up Here's how it works: Anybody can ask a question Anybody can answer The best answers are voted up and rise to the top Calculating standard error and attaching an error bar on ggplot2 r error bars bar chart up vote 4 down vote favorite 1 Given a minimal dataset where am looking for the occurrence of a certain motif within a dataset of 500 observations. with_motif represents obervations with the specified motif and without_motif are observations without the motif. with_motif <- 100 without_motif <- 400 dt <- data.frame(with_motif,without_motif) The following code will plot a bar-chart using ggplot2 library, bar_plot <- ggplot(melt(dt),aes(variable,value)) + geom_bar() + scale_x_discrete(name="with or without") + theme_bw() + opts( panel.grid.major = theme_blank(),title = "", plot.title=theme_text(size=14)) bar_plot I would like to compute a standard error at 95% CI and attach a barchart to the plot. ggplot offers geom_errorbar() but I would be glad to know different ways for deriving the standard errors(deviation) so as to calculate the errorbar limits(CI). r ggplot2 barplot share|improve this question edited Aug 11 '11 at 12:15 mbq 17.8k849103 asked Aug 11 '11 at 10:34 eastafri 2481714 +1, but kindly avoid "plot" as an object name! –
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 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 of 6.2 million programmers, just like you, helping each other. Join them; it only takes a minute: Sign up specify error bars with ggplot and facet_grid up vote 3 down vote favorite I have made a graph with facet_grid to visualize the percentage of litium in each group per treatment on each day. library(ggplot2) library(Rmisc) library(plyr) mus2 <- summarySE(mus, measurevar="litium", groupvars=c("treatment", "group", "day"), na.rm = TRUE) mus2 mus3 <- mus2 mus3$group <- factor(mus3$group) ms.chl<- ggplot(mus3, aes(x=group, y=litium, fill=treatment)) + geom_bar(stat="identity", colour="black") + facet_grid(~day) + theme_bw() ms.chl resulting with this: For that I have two problems: I cant make proper error bars for the litium content PER GROUP. I have tried this, but I only get error bars per treatment. ms.chl + geom_errorbar(aes(ymin=litium-se, ymax=litium+se), size=0.5, width=.25, position=position_dodge(.9)) + facet_grid(~day) I would like to have error bars from the total of each group and after that, my second question is: is it possible to represent the absolute value per group and the percentage only for each treatment? Data set (mus): litium group treatment day 0.009439528 1 Control day1 0.005115057 1 Control day1 0.009742297 1 Control day1 0.016515625 2 Control day1 0.01074537 2 Control day1 0.016300836 2 Control day1 0.009538339 3 Control day1 0.010609746 3 Control day1 0.008928012 3 Control day1 0.009425325 1 Control + bird day1 0.00561831 1 Control + bird day1 0.014622517 1 Control + bird day1 0.017702439 2 Control + bird day1 0.010545045 2 Control + bird day1 0.029109907 2 Control + bird day1 0.013737568 3 Control + bird day1 0.015174405 3 Control + bird day1 0.014583832 3 Control + bird day1 0.009244079 1 Control day2 0.006591033 1 Control day2 0.007592587 1 Control day2 0.013676745 2 Control day2 0.016208676 2 Control day2 0.017593952 2 Control day2 0.014003037 3 Control day2 0.01163581 3 Control day2 0.011643067 3 Control day2 0.009229506 1 Control + bird day2 0.006423714 1 Control + bird day2 0.008653163 1 Control + bird day2 0.012441379 2 Control + bird day2 0.0204346 2 Control + bird day2 0.010017788 2 Control + bird day2 0.009745063 3 Control + bird day2 0.00967963 3 C