GDP与人预期寿命的关系图----R-CFANZ编程社区

单位GDP与寿命的关系统计绘图
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library(ggplot2)
library(gganimate)
theme_set(theme_bw())
library(gapminder)
head(gapminder)
p <- ggplot(
  gapminder, 
  aes(x = gdpPercap, y=lifeExp, size = pop, colour = country)
) +
  geom_point(show.legend = FALSE, alpha = 0.7) +
  scale_color_viridis_d() +
  scale_size(range = c(2, 12)) +
  scale_x_log10() +
  labs(x = "GDP per capital", y = "Life expectancy")
p

通过不同州的时间数据进行转换
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library(ggplot2)
library(gganimate)
theme_set(theme_bw())
library(gapminder)
head(gapminder)
p <- ggplot(
  gapminder, 
  aes(x = gdpPercap, y=lifeExp, size = pop, colour = country)
) +
  geom_point(show.legend = FALSE, alpha = 0.7) +
  scale_color_viridis_d() +
  scale_size(range = c(2, 12)) +
  scale_x_log10() +
  labs(x = "GDP per capital", y = "Life expectancy")
p + transition_time(year) +
  labs(title = "Year: {frame_time}")

根据不同大洲创建不同面:

library(ggplot2)
library(gganimate)
theme_set(theme_bw())
library(gapminder)
head(gapminder)
p <- ggplot(
  gapminder, 
  aes(x = gdpPercap, y=lifeExp, size = pop, colour = country)
) +
  geom_point(show.legend = FALSE, alpha = 0.7) +
  scale_color_viridis_d() +
  scale_size(range = c(2, 12)) +
  scale_x_log10() +
  labs(x = "GDP per capital", y = "Life expectancy")
p + facet_wrap(~continent) +
  transition_time(year) +
  labs(title = "Year: {frame_time}")

让视图跟着每帧数据变
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p + transition_time(year) +
  labs(title = "Year: {frame_time}") +
  view_follow(fixed_y = TRUE)

Show preceding frames with gradual falloff
This shadow is meant to draw a small wake after data by showing the latest frames up to the current. You can choose to gradually diminish the size and/or opacity of the shadow. The length of the wake is not given in absolute frames as that would make the animation susceptible to changes in the framerate. Instead it is given as a proportion of the total length of the animation.

p + transition_time(year) +
  labs(title = "Year: {frame_time}") +
  shadow_wake(wake_length = 0.1, alpha = FALSE)

Static plot

p + transition_time(year) +
  labs(title = "Year: {frame_time}") +
  shadow_mark(alpha = 0.3, size = 0.5)

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Let data gradually appear
Reveal by day (x-axis)

library(ggplot2)
library(gganimate)
theme_set(theme_bw())
library(gapminder)
p <- ggplot(
  airquality,
  aes(Day, Temp, group = Month, color = factor(Month))
) +
  geom_line() +
  scale_color_viridis_d() +
  labs(x = "Day of Month", y = "Temperature") +
  theme(legend.position = "top")
p

p + transition_reveal(Day)

p + 
  geom_point() +
  transition_reveal(Day)

p + 
  geom_point(aes(group = seq_along(Day))) +
  transition_reveal(Day)

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transition_states():

library(dplyr)
mean.temp <- airquality %>%
  group_by(Month) %>%
  summarise(Temp = mean(Temp))
mean.temp
p <- ggplot(mean.temp, aes(Month, Temp, fill = Temp)) +
  geom_col() +
  scale_fill_distiller(palette = "Reds", direction = 1) +
  theme_minimal() +
  theme(
    panel.grid = element_blank(),
    panel.grid.major.y = element_line(color = "white"),
    panel.ontop = TRUE
  )
p

library(dplyr)
mean.temp <- airquality %>%
  group_by(Month) %>%
  summarise(Temp = mean(Temp))
mean.temp
p <- ggplot(mean.temp, aes(Month, Temp, fill = Temp)) +
  geom_col() +
  scale_fill_distiller(palette = "Reds", direction = 1) +
  theme_minimal() +
  theme(
    panel.grid = element_blank(),
    panel.grid.major.y = element_line(color = "white"),
    panel.ontop = TRUE
  )
p + transition_states(Month, wrap = FALSE) +
  shadow_mark()

enter_grow() + enter_fade()

p + transition_states(Month, wrap = FALSE) +
  shadow_mark() +
  enter_grow() +
  enter_fade()

参考资料：

https://www.datanovia.com/en/blog/gganimate-how-to-create-plots-with-beautiful-animation-in-r/
https://cloud.tencent.com/developer/article/1675209
TED：https://www.ted.com/talks/hans_rosling_the_best_stats_you_ve_ever_seenlanguage=zh-TW