Creating a grouped barplot of multiple variables with two Y axes in R

[sarkar66]

Hi, I have the following data set which includes four variables under three group.
Df<-data_frame(group= c("A", "B", "C"),
Co= c(0.021, 0.013,0.03),
Se =c(0.061, 0.101, 0.300),
Fe = c(62.663, 53.500,60.000)
Zn = c( 5.329, 8.400, 3.000))

with this above data I would like to create a bar plot with two y axis one for Co, Se and one for Fe and Zn. Please help me how to do that.
Here, I am giving a link of similar topic but this data icluded only two variables

Creating a grouped barplot with two Y axes in R

Hello everyone, I have the following data frame which consists of visual / sightings per hour (SPH) and acoustic / clicks per hour (CPH) data sets for a time span of 8 weeks. I'd like to to have a grouped bar plot which groups the two values for one week together. So e.g. it's 2.676 sightings/h in week 1 and 75.35 clicks/h in week 1. Because of the different units for both variables I also need two y-axes, one for sightings/h on the left and one for clicks/h on the right. data.frame(Week = c(1, 2, 3, 4, 5, 6, 7, 8), SPH = c(2.676, 2.660, 4.175, 2.134, 3.742, 1.395, 4.739, 2.756), CPH = c(75.35, 29.58, 20.51, 80.43, 97.94, 85.39, 168.61, 142.19)) I tried to create a matrix to plot the …

[jms]

Hey and welcome to the forum!

You can essentially use the same method that has been used in the thread you have linked in your post.

Here is the method presented there adjusted to your problem.

library(tidyverse)
Df<-data.frame(group= c("A", "B", "C"),
               Co= c(0.021, 0.013,0.03),
               Se =c(0.061, 0.101, 0.300),  
               Fe = c(62.663, 53.500,60.000),
               Zn = c( 5.329, 8.400, 3.000))  


Df%>%pivot_longer(-group, names_to = "Element")%>%
  mutate(scaled_value = ifelse(Element == "Co" | Element == "Se", value * 200, value))%>%
  ggplot(aes(x=group, y = scaled_value, fill = Element))+
  geom_col(position = "dodge")+
  scale_y_continuous(sec.axis = sec_axis(~ . / 200, name = "Co and Se"))+
  labs(y="Fe and Zn")

^{Created on 2022-11-15 with reprex v2.0.2}

However, I personally would be carefull with such a plot, as it is not easy to identify which of the y axes applies on which of the variables. You could try to improve it by reordering the the bars so that Zinc and Iron are on the left and Selenium and Copper appear on the right side of each group; for example by adding Element = factor(Element, levels = c("Fe", "Zn", "Co", "Se")) into the mutate() function.

Alternatively, you could use ggplot's faceting functions to create a plot that I think is easier to interpret (but of course I don't know what you are intending to show with your plot). Here is a way you could use facets to show all four elements:

library(tidyverse)
Df<-data.frame(group= c("A", "B", "C"),
               Co= c(0.021, 0.013,0.03),
               Se =c(0.061, 0.101, 0.300),  
               Fe = c(62.663, 53.500,60.000),
               Zn = c( 5.329, 8.400, 3.000))  

Df%>%pivot_longer(-group, names_to = "Element")%>%
  mutate(scale = ifelse(Element == "Co" | Element == "Se", "Co and Se", "Fe and Zn"))%>%
  ggplot(aes(x=group, y = value, fill = Element))+
  geom_col(position = "dodge")+
  facet_wrap(~scale, scales = "free")

^{Created on 2022-11-15 with reprex v2.0.2}

I hope those suggestions are helpful to you!

[sarkar66]

Dear jms,
It's worked perfectly. Thank you very much.