%>% 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.
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().
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