Ordering bar plots with ggplot2 according to their size, i.e. numerical value

Question

This question asks about ordering a bar graph according to an unsummarized table. I have a slightly different situation. Here\'s part of my original data:

ex         


        

Answer 1

With newer tidyverse functions, this becomes much more straightforward (or at least, easy to read for me):

library(tidyverse)

d %>%
  mutate_at("pvs_id", as.factor) %>%
  mutate(pvs_id = fct_reorder(pvs_id, mqs)) %>%
  gather(variable, value, c(mqs, imcs)) %>% 
  ggplot(aes(x = pvs_id, y = value)) + 
    geom_col(aes(fill = variable), position = position_dodge())

What it does is:

• create a factor if not already
• reorder it according to mqs (you may use desc(mqs) for reverse-sorting)
• gather into individual rows (same as melt)
• plot as geom_col (same as geom_bar with stat="identity")

Answer 2

It's all in making

pvs_id a factor and supplying the appropriate levels to it:

dat$pvs_id <- factor(dat$pvs_id, levels = dat[order(-dat$mqs), 2])

m = melt(dat, id.var="pvs_id", measure.var=c("mqs","imcs"))

ggplot(m, aes(x=pvs_id, y=value))+ 
    geom_bar(aes(fill=variable), position="dodge", stat="identity")

This produces the following plot:

EDIT: Well since pvs_id was numeric it is treated in an ordered fashion. Where as if you have a factor no order is assumed. So even though you have numeric labels pvs_id is actually a factor (nominal). And as far as dat[order(-dat$mqs), 2] is concerned the order function with a negative sign orders the data frame from largest to smallest along the variable mqs. But you're interested in that order for the pvs_id variable so you index that column which is the second column. If you tear that apart you'll see it gives you:

> dat[order(-dat$mqs), 2]
[1] 6 2 0 5 7 4 8 3 1

Now you supply that to the levels argument of factor and this orders the factor as you want it.