Data Science Desktop Survival Guide by Graham Williams
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Flipped Mean Confidence Intervals

20200822

ds %>%
  filter(location %in% (ds$location %>% unique %>% sample(20))) %>%
  mutate(location=factor(location,
                         levels=location %>% unique() %>%
                                   sort() %>% rev())) %>%
  ggplot(aes(location, temp_3pm, fill=location)) +
  stat_summary(fun="mean", geom="bar") +
  stat_summary(fun.data="mean_cl_normal", geom="errorbar", width=0.35) +
  theme(legend.position="none") +
  labs(x=vnames["temp_3pm"], y=vnames["location"]) +
  coord_flip()

Various annotations can be added to plots. In this example we include a confidence interval around the average values.