How to get a barplot with several variables side by side grouped by a factor

Question

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      In the end I want to get a barplot like this    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

User · Accepted Answer

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

Get rid of the Group.1 column

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

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

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")

enter image description here

User · Answer

You can plot the means without resorting to external calculations and additional tables using stat summary       In fact  stat summary      was designed for exactly what you are doing   library ggplot2  library reshape2               for melt      gg  lt - melt df id  gender       df is your original table ggplot gg  aes x variable  y value  fill factor gender         stat summary fun y mean  geom  bar  position position dodge 1        scale color discrete  Gender     stat summary fun ymin min fun ymax max geom  errorbar                  color  grey80  position position dodge 1   width  2      To add  error bars  you cna also use stat summary       here  I m using the min and max value rather than sd because you have so little data    ggplot gg  aes x variable  y value  fill factor gender         stat summary fun y mean  geom  bar  position position dodge 1        stat summary fun ymin min fun ymax max geom  errorbar                  color  grey40  position position dodge 1   width  2      scale fill discrete  Gender

User · Answer

Using reshape2 and dplyr  Your data   df  lt - read table text   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   header TRUE    Getting data into correct form   library reshape2  library dplyr  df melt  lt - melt df  id  gender   bar  lt - group by df melt  variable  gender    summarise mean mean value     Plotting   library ggplot2  ggplot bar  aes x variable  y mean  fill factor gender       geom bar position  dodge   stat  identity

[r] How to get a barplot with several variables side by side grouped by a factor

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