%>% 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") + theme(legend.position="none") + labs(x=vnames["temp_3pm"], y=vnames["location"]) + coord_flip()
Labels will sometimes appear in the reverse order to that required, particularly in this flipped bar chart. We can explicitly reorder the levels to ensure the plot labels are in a more natural (alphabetic) order for the human reader. We use dplyr::mutate() within a pipeline to create a factor with the levels in the desired order passing that on to ggplot2::ggplot().
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