如何获得按因子分组的多个变量并排的条形图 [英] How to get a barplot with several variables side by side grouped by a factor

问题描述

我有一个数据集，如下所示.我正在尝试使用分组变量性别制作一个条形图，所有变量并排在 x 轴上(按性别分组为不同颜色的填充物)，以及 y 轴上变量的平均值(基本上代表百分比)

I have a dataset which looks like this one below. I am trying to make a barplot with the grouping variable gender, with all the variables side by side on the x axis (grouped by gender as filler with different colors), and mean values of variables on the y axis (which basically represents percentages)

tea                coke            beer             water           gender
14.55              26.50793651     22.53968254      40              1
24.92997199        24.50980392     26.05042017      24.50980393     2
23.03732304        30.63063063     25.41827542      20.91377091     1   
225.51781276       24.6064623      24.85501243      50.80645161     1
24.53662842        26.03706973     25.24271845      24.18358341     2   

最后我想得到这样的条形图

In the end I want to get a barplot like this

任何建议如何做到这一点?我进行了一些搜索，但我只找到了 x 轴上因子的示例，而不是按因子分组的变量.任何帮助将不胜感激！

any suggestions how to do that? I made some searches but I only find examples for factors on the x axis, not variables grouped by a factor. any help will be appreciated!

推荐答案

您可以使用聚合来计算均值:

You can use aggregate to calculate the means:

means<-aggregate(df,by=list(df$gender),mean)
Group.1      tea     coke     beer    water gender
1       1 87.70171 27.24834 24.27099 37.24007      1
2       2 24.73330 25.27344 25.64657 24.34669      2

去掉 Group.1 列

Get rid of the Group.1 column

means<-means[,2:length(means)]

然后您将数据重新格式化为长格式:

Then you have reformat the data to be in long format:

library(reshape2)
means.long<-melt(means,id.vars="gender")
  gender variable    value
1      1      tea 87.70171
2      2      tea 24.73330
3      1     coke 27.24834
4      2     coke 25.27344
5      1     beer 24.27099
6      2     beer 25.64657
7      1    water 37.24007
8      2    water 24.34669

最后，您可以使用 ggplot2 来创建您的绘图:

Finally, you can use ggplot2 to create your plot:

library(ggplot2)
ggplot(means.long,aes(x=variable,y=value,fill=factor(gender)))+
  geom_bar(stat="identity",position="dodge")+
  scale_fill_discrete(name="Gender",
                      breaks=c(1, 2),
                      labels=c("Male", "Female"))+
  xlab("Beverage")+ylab("Mean Percentage")

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