R Error Bars Ggplot2
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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 you want to override the plot defaults. stat The statistical transformation to use on the data summaryse r for this layer. position The position adjustment to use for overlappling points on this layer
R Calculate Standard Error
... other arguments passed on to layer. This can include aesthetics whose values you want to set, not map. See href='layer.html'>layerGgplot Confidence Interval
Ggplot2 Stat_summary
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 barplot with error bars r 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 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 p + geom_pointrange(limits) p + geom_cross
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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 http://stackoverflow.com/questions/32842923/specify-error-bars-with-ggplot-and-facet-grid 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 https://egret.psychol.cam.ac.uk/statistics/R/graphs2.html 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 error bars 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 r error bars 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
error bars Saving a graph to PDF, or PNG, or... Graph with free-floating SED bar Bar graph with error bars Another bar graph, with annotations Graph with multiple axis breaks Two-panel plot with horizontal and vertical error bars Prerequisite The ggplot2 library: library(ggplot2) If that doesn’t work, use install.packages("ggplot2") to install it, then retry. Not quite a prerequisite: add the ability to have left/bottom (without top/right) axes It’s hard to get ggplot to draw left and bottom axes only. Some use a post-processing hack (see http://wilke.openwetware.org/Creating_figures.html). I tried switching off all borders, using opts(panel.border = theme_blank()) and then using geom_hline(y=0) and geom_hline(y=0) to draw axes, which is OK, but it’s hard to get them positioned correctly. However, ggplot2 is open-source. So we can explore it: sudo apt-get install git to get the appropriate source code tools, then git clone https://github.com/hadley/ggplot2.git to fetch the source. And looking in theme-elements.r we can see the sort of thing to aim for. So we can create some code snippets which we can include in one line from rnc_ggplot2_border_themes_2011_03_17.r or rnc_ggplot2_border_themes_2013_01.r, like so: # For versions of ggplot2 around 0.8.7 / prior to Jan 2013: source("http://egret.psychol.cam.ac.uk/statistics/R/extensions/rnc_ggplot2_border_themes_2011_03_17.r") # For ggplot2 version 0.9.3 / from Jan 2013 onwards: source("http://egret.psychol.cam.ac.uk/statistics/R/extensions/rnc_ggplot2_border_themes_2013_01.r") This provides a number of possibilities but the theme_border() version is probably the easier to use. Its use is illustrated below: see opts( panel.border = theme_border(...) ). Data files used in these examples These files are all comma-separated value (CSV) text files: PhD_fig21A.csv PhD_fig37B.csv PhD_fig22D.csv PhD_fig23.csv PhD_fig28C.csv MD_fig30A.csv MD_fig30B.csv Let’s load them all in, to begin with: phdfig37b = read.table("PhD_fig37B.csv", header=TRUE, sep=",", na.strings="NA", dec=".", strip.white=TRUE) phdfig21a = read.table("PhD_fig21A.csv", header=TRUE, sep=",", na.strings="NA", dec=".", strip.white=TRUE) phdfig22d = read.table("PhD_fig22D.csv", header=TR