Data Science Desktop Survival Guide
by Graham Williams |
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Pie Chart |
Raw
ds %>%
group_by(rain_tomorrow) %>% count() %>% ungroup() %>% mutate(per=round(`n`/sum(`n`), 2)) %>% mutate(label=paste(rain_tomorrow, percent(per))) %>% arrange(per) %>% ggplot(aes(x=1, y=per, fill=rain_tomorrow)) + geom_bar(stat="identity") + coord_polar(theta='y') + theme_void() + theme(legend.position="none") + geom_text(aes(x=1, y=cumsum(per)-per/2, label=label), size=8)
A pie chart is a popular circular plot showing the relative proportions through angular slices. Generally, pie charts are not recommended, particularly for multiple wedges, because humans generally have difficulty perceiving the relative angular differences between slices. For two or three slices it may be argued that the pie chart is just fine, particularly if further information is provided, such as labelling the slices with their sizes. See also the illustrated tour and pie chart papers for explorations of the utility of pie charts.
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