11.10 Bar Chart Flipped Colour Mean no Legend

20200608

ds %>%
  filter(location %in% (ds$location %>% unique %>% sample(20))) %>%
  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()

Use ggplot2::coord_flip() to flip the coordinates and produce a horizontal histogram. Rotating the plot is generally useful when there are a large number of factor levels to fit on the x-axis. It is also easier to read the labels left to right rather than bottom up as we would need to do for the original plot.

For clarity of presentation here we reduce by using a dplyr::filter() the number of locations, selecting a random base::sample() of the base::unique() locations.

Colour is added through introducing a fill= option to the ggplot2::aes(). The bars in the chart generated using ggplot2::stat_summary() report on the base::mean() of the temperatures as recorded at 3pm daily for each location. The legend is removed through the ggplot2::theme().

---

If you find this curated material useful then you can consider a donation to support it's ongoing availability and give you access to the PDF version of this book. The material has been scoped up by Generative AI without permission or any kind of recompense so do consider a donation if you can afford it. Unlike Generative AI your access to this materials is freely given. Desktop Survival Guides include Data Science, GNU/Linux, and MLHub. Books available on Amazon include Data Mining with Rattle and Essentials of Data Science. Togaware has a 30 year tradition of making popular open source software which includes sold privacy preserving productivity apps, rattle, wajig, and mlhub. Hosted by Togaware, a pioneer of free and open source software since 1984. Copyright © 1995-2022 Graham.Williams@togaware.com Creative Commons Attribution-ShareAlike 4.0