How to use geom_bar() to create two grouped columns in R

Question

There has got to be an easy way to create one set of grouped bars for aware column and a another set of grouped bars for serious column with the individual bars within each group being the value for the respective regions. Final image should look similar to attached image. Thanks!

data I'm working with

Image I'm seeking approximately

by_region <- country_obs_df %>%
  group_by(Region) %>%
  summarize(
    #region_avg_gdp = GDPperUS,
    #region_avg_co2 = CO2emi,
    #region_avg_pop = Population.2008,
    region_avg_aware = mean(Aware),
    region_avg_serious = mean(Serious)
  )
ggplot(by_region) +
  geom_col(mapping = aes(fill = Region, x = Region, y=region_avg_aware), position = "dodge") +
  labs(y = "Percent")

Answer 1

For sure, it is possible, you have to reformat your data to long so that you have the required variables in a row format in order to be plotted. Here the code using the data screenshot you shared:

library(tidyverse)
#Data
df <- data.frame(Region=c('Africa','Asia','Europe','Europe (North America)',
                          'Europe (Oceania)','Latin America & Caribbean'),
                 region_avg_aware=c(39.9,60.9,88.3,96.6,97.3,63.8),
                 region_avg_serious=c(82.3,76.3,67.7,71.1,78.2,93.8))
#Plot
df %>% pivot_longer(-Region) %>%
  ggplot(aes(x=name,y=value,group=Region,fill=Region))+
  geom_bar(stat = 'identity',position = position_dodge(0.9))+
  theme_bw()+
  theme(axis.text = element_text(color='black',face='bold'),
        axis.title = element_text(color='black',face='bold'),
        legend.text = element_text(color='black',face='bold'),
        legend.title = element_text(color='black',face='bold'),
        panel.grid = element_blank())+
  xlab('Variable')

Output:

Answer 2

An option is to pivot to 'long' format then, use geom_col

library(dplyr)
library(ggplot2)
library(tidyr)
by_region %>%
    pivot_longer(cols = -Region, names_to = 'region_avg') %>%
    ggplot(aes(x = region_avg, y = value, fill = Region)) +
         geom_col( position = "dodge") +
         labs(y = "Percent")

-output

data

by_region <- structure(list(Region = c("Africa", "Asia", "Europe", "Europe (North America)", 
"Europe (Oceania)", "Latin America & Caribbean"), region_avg_aware = c(39.9, 
60.9, 88.3, 96.6, 97.3, 63.8), region_avg_serious = c(82.3, 76.3, 
67.7, 71.1, 78.2, 93.8)), class = "data.frame", row.names = c(NA, 
-6L))