Cleveland dot plot in ggplot2

Question

In the recent TIMSS report that I happened to come across, there's a plot (shown below) that in my opinion is very communicative. I've read that such plots are called Cleveland dot plots, though this one adds confidence intervals as well. I was wondering if it can be reproduced in ggplot2 or matplotlib. All hints are welcome.
_{(source: timss2015.org)}

Answer 1

Using the iris data set:

library(dplyr)
library(ggplot2)

plot_data <- iris %>% 
  group_by(Species) %>% 
  summarise_each(funs(mean, sd, n(), q95=quantile(., 0.95), q75=quantile(., 3/4), q25=quantile(., 1/4),  q5 = quantile(., 0.05)), Sepal.Length) %>% 
  mutate(se = sd/sqrt(n),
         left95 = mean - 2*se,
         right95 = mean + 2*se)


ggplot(plot_data, aes(x = Species, y = mean)) +
  geom_crossbar(aes(ymin = q5, ymax = q95), fill = "aquamarine1",  color = "aquamarine1", width = 0.2) +
  geom_crossbar(aes(ymin = q25, ymax = q75), fill = "aquamarine4",  color = "aquamarine4", width = 0.2) +
  geom_crossbar(aes(ymin = left95, ymax = right95), fill = "black", color = "black", width = 0.2) +
  coord_flip() +
  theme_minimal()

This should give you the gist of how to use ggplot2 to accomplish this. The data you provided can be easily used, without the dplyr summarizing.