使用ggplot和facet_grid指定错误栏 [英] specify error bars with ggplot and facet_grid
问题描述
我用facet_grid制作了一个图表，以可视化每天每一组中每组中锂的百分比.
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
结果:
为此，我有两个问题:
我不能为PER GROUP的锂含量设置适当的误差线.我已经尝试过了，但是每次治疗我只会得到错误条.
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)
我想从每个组的总数中得出误差线
I would like to have error bars from the total of each group
然后，我的第二个问题是:是否可以代表每组的绝对值和仅代表每种治疗的百分比?
and after that, my second question is: is it possible to represent the absolute value per group and the percentage only for each treatment?
数据集(亩):
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 Control + bird day2
0.010291306 3 Control + bird day2
0.009466604 1 Fence day2
0.019611081 2 Fence day2
0.006796444 2 Fence day2
0.018928695 2 Fence day2
0.007787736 3 Fence day2
0.009409897 3 Fence day2
推荐答案
第一个也是最简单的解决方案是使条形图并排而不是堆叠.然后，您唯一需要更改的代码就是将position="dodge"添加到geom_bar()并按需运行其余代码.这样做还有一个好处，就是可以直接比较不同条形的高度，并且避免将误差线放在条形的中间.
The first and easiest solution would be to make your bar plot side-by-side instead of stacked. Then the only thing you need to change in your code is to add position="dodge" to your geom_bar() and run the rest of your code as you have it. This has the added benefit of being able to compare the heights of the different bars directly and avoids placing error bars in the middle of a bar.
ms.chl<- ggplot(mus3, aes(x=group, y=litium, fill=treatment)) +
geom_bar(stat="identity", colour="black",position="dodge") +
facet_grid(~day) + theme_bw()
ms.chl + geom_errorbar(aes(ymin=litium-se, ymax=litium+se), size=0.5,
width=.25,position=position_dodge(.9)) +
facet_grid(~day)
要在堆叠的条形图上添加误差线，必须确保这些条的中心位于litium的累加总和上.为此，您可以在ave()中使用cumsum():
To add error bars on a stacked bar plot, you have to have make sure the bars are centered on the cumulative sum of litium. For this, you can use cumsum() within ave():
mus3 <- within(mus3,lit2 <- ave(litium,group,day,FUN=cumsum))
然后在呼叫geom_errorbar()时不要使用lit2而不是litium.
Then use lit2 instead of litium when you call geom_errorbar() and don't dodge.
ms.chl<- ggplot(mus3, aes(x=group, y=litium, fill=treatment)) +
geom_bar(stat="identity", colour="black") + facet_grid(~day) + theme_bw()
ms.chl + geom_errorbar(aes(ymin=lit2-se, ymax=lit2+se), size=0.5,
width=.25) + facet_grid(~day)
如果您只想要该组的误差线，则必须获取整个组而不是治疗中的组的误差，但是您不能仅仅将其直接添加到基于整个组的平均值上，因为这些是均值，并且堆积的条形图具有均值的总和，所以您必须对mus3中的均值求和.
And if you just want the error bars for the group, then you have to get the errors for the whole group and not the group within treatment, but you can't just add that straight to the means based on the whole group, because those are means and the stacked bar plot has the sum of the means, so you have to sum the means from mus3.
musgroup <- summarySE(mus, measurevar="litium",
groupvars=c("group", "day"), na.rm = TRUE)
musgroupsum <- ddply(mus3,.(group,day),summarize,lit2 = sum(litium))
mus4 <- merge(musgroup,musgroupsum)
ms.chl<- ggplot() +
geom_bar(data=mus3, aes(x=group, y=litium, fill=treatment),
stat="identity", colour="black") + facet_grid(~day) + theme_bw()
ms.chl + geom_errorbar(data=mus4,aes(x=group,ymin=lit2-se, ymax=lit2+se),
size=0.5, width=.25)
在这一点上，它开始变得有点荒谬.堆积均值不是分组均值-它们是分组均值的总和，但误差是针对分组均值的.当您查看该图时，误差线相对于它们所代表的均值而言似乎较小，因为它们居中的位置远高于其应有的位置.似乎您正在寻找的是群体均值的表示形式，它使您可以看到每种治疗方法对该群体均值的贡献.一种显示方法是缩放条形图大小，以使累积总和以每个组的均值为中心.
At this point, though, it starts getting a little nonsensical. The stacked means are not the group means--they are the sum of the group means, but the error is for the group mean. When you look at the figure the error bars will seem smaller in relation to the mean they represent because they are centered much higher than they ought to be. It seems like what you are looking for is a representation of the group mean that allows you to see the contribution of each of the treatments to that group mean. One way to show this is to scale the bar plot size so that the cumulative sum is centered on the proper mean for each of the groups.
mus3 <- within(mus3,lit3 <- ave(litium,group,day,FUN=function(x) x/length(x)))
ms.chl<- ggplot() +
geom_bar(data=mus3, aes(x=group, y=lit3, fill=treatment),
stat="identity", colour="black") + facet_grid(~day) +
theme_bw() + ylab("litium")
ms.chl + geom_errorbar(data=mus4,aes(x=group,ymin=litium-se, ymax=litium+se),
size=0.5,width=.25)
这篇关于使用ggplot和facet_grid指定错误栏的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
