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On bubbles and trees 💫

Teun van den Brand делает просто волшебные дополнения к ggplot2, в частности, библиотека {legendry} теперь позволяет делать пузырьковые легенды для графиков.


library(legendry)

gapminder::gapminder |>
dplyr::filter(year == max(year)) |>
ggplot(aes(gdpPercap, lifeExp, size = pop,
fill = continent)) +
geom_point(pch = 21, alpha = 0.8) +
scale_size_area(
limits = c(0, NA), max_size = 20,
breaks = c(0, 100, 500, 1000)*1e6,
labels = c(0, "100M", "500M", "1B"),
guide = guide_circles(vjust = 1)
) +
scale_fill_discrete(guide =
guide_legend(override.aes =
list(size = 4, alpha = 0.8))) +
scale_x_log10() +
labs(
x = "ВВП на душу населения",
y = "Ожидаемая продолжительность жизни",
fill = "Континент",
size = "Население"
)


Это должно быть по умолчанию в {ggplot2}!



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On bubbles and trees 💫

Teun van den Brand делает просто волшебные дополнения к ggplot2, в частности, библиотека {legendry} теперь позволяет делать пузырьковые легенды для графиков.


library(legendry)

gapminder::gapminder |>
dplyr::filter(year == max(year)) |>
ggplot(aes(gdpPercap, lifeExp, size = pop,
fill = continent)) +
geom_point(pch = 21, alpha = 0.8) +
scale_size_area(
limits = c(0, NA), max_size = 20,
breaks = c(0, 100, 500, 1000)*1e6,
labels = c(0, "100M", "500M", "1B"),
guide = guide_circles(vjust = 1)
) +
scale_fill_discrete(guide =
guide_legend(override.aes =
list(size = 4, alpha = 0.8))) +
scale_x_log10() +
labs(
x = "ВВП на душу населения",
y = "Ожидаемая продолжительность жизни",
fill = "Континент",
size = "Население"
)


Это должно быть по умолчанию в {ggplot2}!

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