演示数据集
library(gapminder) head(gapminder)
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## # A tibble: 6 x 6 ## country continent year lifeExp pop gdpPercap ## ## 1 Afghanistan Asia 1952 28.8 8425333 779. ## 2 Afghanistan Asia 1957 30.3 9240934 821. ## 3 Afghanistan Asia 1962 32.0 10267083 853. ## 4 Afghanistan Asia 1967 34.0 11537966 836. ## 5 Afghanistan Asia 1972 36.1 13079460 740. ## 6 Afghanistan Asia 1977 38.4 14880372 786.
静态图
<- ggplot(\n gapminder, \n aes(x = gdpPercap, y=lifeExp, size = pop, colour = country)\n ) +\n geom_point(show.legend = FALSE, alpha = 0.7) +\n scale_color_viridis_d() +\n scale_size(range = c(2, 12)) +\n scale_x_log10() +\n labs(x = \"GDP per capita\", y = \"Life expectancy\")\np","classes":{"has":1},"lang":""}" data-cke-widget-upcasted="1" data-cke-widget-keep-attr="0" data-widget="codeSnippet">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 capita", y = "Life expectancy") p
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基本
状态之间的过渡长度将设置为与它们之间的实际时间差相对应。
标签变量：frame_time。给出当前帧所对应的时间。
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创建面：
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让视图跟随数据在每帧中
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逐步衰减
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显示原始数据作为背景
您可以根据需要显示过去和/或将来的原始数据并设置其样式。
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静态图
<- ggplot(\n airquality,\n aes(Day, Temp, group = Month, color = factor(Month))\n ) +\n geom_line() +\n scale_color_viridis_d() +\n labs(x = \"Day of Month\", y = \"Temperature\") +\n theme(legend.position = \"top\")\np","classes":{"has":1},"lang":""}" data-cke-widget-upcasted="1" data-cke-widget-keep-attr="0" data-widget="codeSnippet">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
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让数据逐渐出现
按天显示（x轴）
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在数据的几个不同阶段之间进行转换
数据准备：
<- airquality %>%\n group_by(Month) %>%\n summarise(Temp = mean(Temp))\nmean.temp","classes":{"has":1},"lang":""}" data-cke-widget-upcasted="1" data-cke-widget-keep-attr="0" data-widget="codeSnippet">library(dplyr) mean.temp <- airquality %>% group_by(Month) %>% summarise(Temp = mean(Temp)) mean.temp
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## # A tibble: 5 x 2 ## Month Temp ## ## 1 5 65.5 ## 2 6 79.1 ## 3 7 83.9 ## 4 8 84.0 ## 5 9 76.9
创建平均温度的条形图：
<- ggplot(mean.temp, aes(Month, Temp, fill = Temp)) +\n geom_col() +\n scale_fill_distiller(palette = \"Reds\", direction = 1) +\n theme_minimal() +\n theme(\n panel.grid = element_blank(),\n panel.grid.major.y = element_line(color = \"white\"),\n panel.ontop = TRUE\n )\np","classes":{"has":1},"lang":""}" data-cke-widget-upcasted="1" data-cke-widget-keep-attr="0" data-widget="codeSnippet">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
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transition_states（）：
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enter_grow（）+ enter_fade（）
保存动画
如果需要保存动画以备后用，可以使用该anim_save()功能。
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