hide gganimate

eda_nobel.Rmd

@@ -161,7 +161,7 @@ df %>%
 
 
 让图骚动起来吧
-```{r eda-nobel-14}
+```{r eda-nobel-14, eval=FALSE}
 library(gganimate) # install.packages("gganimate", dependencies = T)
 
 df %>%

eda_vaccine_effectiveness.Rmd

@@ -43,6 +43,8 @@ $$
 library(tidyverse)
 library(tidybayes)
 library(rstan)
+  rstan_options(auto_write = FALSE)
+  options(mc.cores = 4)
 ```
 
 然后，我们建立如下数学模型：

ggplot2_gganimate.Rmd

@@ -1,7 +1,7 @@
 # ggplot2之让你的数据骚动起来 {#ggplot2-gganimate}
 
 
-这节课，我们讲如何让我们的图动起来。
+这节课，我们讲如何让我们的图动起来。（因为渲染需要花费很长时间，所以文档中的动图代码都没有执行。）
 
 
 ## 为什么要使用动图
@@ -21,15 +21,15 @@ install.packages("gganimate")
 
 
 ### 先来一张静态图
-```{r ggplot2-gganimate-2}
+```{r ggplot2-gganimate-2, eval=FALSE}
 library(tidyverse)
 library(covdata) # remotes::install_github("kjhealy/covdata")
 library(gganimate)
 ```
 
 
 
-```{r ggplot2-gganimate-3}
+```{r ggplot2-gganimate-3, eval=FALSE}
 covdata::covnat %>%
   dplyr::filter(iso3 == "USA") %>%
   dplyr::filter(cu_cases > 0) %>%
@@ -44,7 +44,7 @@ covdata::covnat %>%
 
 让它动起来，我们只需要增加一行代码！
 
-``` {r}
+``` {r, eval=FALSE}
 covdata::covnat %>%
   dplyr::filter(iso3 == "USA") %>%
   dplyr::filter(cu_cases > 0) %>%
@@ -60,23 +60,23 @@ covdata::covnat %>%
 
 ### 相对复杂点的例子
 
-```{r ggplot2-gganimate-4}
+```{r ggplot2-gganimate-4, eval=FALSE}
 library(datasauRus)
 ggplot(datasaurus_dozen) +
   aes(x, y, color = dataset) +
   geom_point()
 ```
 
 用分面展示
-```{r ggplot2-gganimate-5}
+```{r ggplot2-gganimate-5, eval=FALSE}
 ggplot(datasaurus_dozen) +
   aes(x, y, color = dataset) +
   geom_point() +
   facet_wrap(~dataset)
 ```
 
 可以用动图展示
-```{r ggplot2-gganimate-6}
+```{r ggplot2-gganimate-6, eval=FALSE}
 ggplot(datasaurus_dozen) +
   aes(x, y, color = dataset) +
   geom_point() +
@@ -110,20 +110,20 @@ ggplot(datasaurus_dozen) +
 ### transition_states
 
 - `transition_states(states = )`, 这里的参数states往往带有分组信息，可以等价于静态图中的分面。
-```{r ggplot2-gganimate-7}
+```{r ggplot2-gganimate-7, eval=FALSE}
 diamonds %>%
   ggplot(aes(carat, price)) +
   geom_point()
 ```
 
-```{r ggplot2-gganimate-8}
+```{r ggplot2-gganimate-8, eval=FALSE}
 diamonds %>%
   ggplot(aes(carat, price)) +
   geom_point() +
   facet_wrap(vars(color))
 ```
 
-```{r ggplot2-gganimate-9}
+```{r ggplot2-gganimate-9, eval=FALSE}
 diamonds %>%
   ggplot(aes(carat, price)) +
   geom_point() +
@@ -134,7 +134,7 @@ diamonds %>%
 
 - `transition_time(time = )`, 这里的time一般认为是**连续**的值，相比于`transition_states`，没有了`transtion_length`这个选项，是因为`transtion_length`默认为time. 事实上，`transition_time`是`transition_states`的一种特例，但其实也有分组的要求
 
-```{r ggplot2-gganimate-10}
+```{r ggplot2-gganimate-10, eval=FALSE}
 p <- gapminder::gapminder %>%
   ggplot(aes(x = gdpPercap, y = lifeExp, size = pop, colour = country)) +
   geom_point(alpha = 0.7, show.legend = FALSE) +
@@ -147,7 +147,7 @@ p <- gapminder::gapminder %>%
 p
 ```
 
-```{r ggplot2-gganimate-11}
+```{r ggplot2-gganimate-11, eval=FALSE}
 anim <- p +
   transition_time(time = year) +
   labs(title = "year: {frame_time}")
@@ -157,15 +157,15 @@ anim
 ### transition_reveal
 - `transition_reveal(along =  )`,  along 这个词可以看出，它是按照某个变量**依次**显示的意思，比如顺着x轴显示
 
-```{r ggplot2-gganimate-12}
+```{r ggplot2-gganimate-12, eval=FALSE}
 ggplot(data = economics) +
   aes(x = date, y = unemploy) +
   geom_line()
 ```
 
 
 
-```{r ggplot2-gganimate-13}
+```{r ggplot2-gganimate-13, eval=FALSE}
 ggplot(economics) +
   aes(x = date, y = unemploy) +
   geom_line() +
@@ -178,7 +178,7 @@ ggplot(economics) +
 ### transition_filter
 
 - `transition_filter( 至少2个筛选条件，transition_length = ,   filter_length =)`, 动图将会在这些筛选条件对应的子图之间转换
-```{r ggplot2-gganimate-14}
+```{r ggplot2-gganimate-14, eval=FALSE}
 diamonds %>%
   ggplot(aes(carat, price)) +
   geom_point() +
@@ -196,7 +196,7 @@ diamonds %>%
 
 - `transition_layers()`: 依次显示每个图层
 
-```{r ggplot2-gganimate-15}
+```{r ggplot2-gganimate-15, eval=FALSE}
 mtcars %>%
   ggplot(aes(mpg, disp)) +
   geom_point() +
@@ -225,7 +225,7 @@ mtcars %>%
 
 动画过程中，绘图窗口怎么变化呢？
 
-```{r views-tbl, echo=FALSE}
+```{r views-tbl, echo=FALSE, eval=FALSE}
 tribble(
   ~Function, ~Description,
   "view_follow", "完全跟随当前数据的范围",
@@ -238,7 +238,7 @@ tribble(
 
 ### view_follow
 
-```{r ggplot2-gganimate-16}
+```{r ggplot2-gganimate-16, eval=FALSE}
 ggplot(iris, aes(Sepal.Length, Sepal.Width)) +
   geom_point() +
   labs(title = "{closest_state}") +
@@ -265,15 +265,15 @@ ggplot(iris, aes(Sepal.Length, Sepal.Width)) +
 
 ### shadow_wake()
 
-```{r ggplot2-gganimate-17}
+```{r ggplot2-gganimate-17, eval=FALSE}
 p +
   transition_time(time = year) +
   labs(title = "year: {frame_time}") +
   shadow_wake(wake_length = 0.1, alpha = FALSE)
 ```
 
 
-```{r ggplot2-gganimate-18}
+```{r ggplot2-gganimate-18, eval=FALSE}
 ggplot(iris, aes(Petal.Length, Sepal.Length)) +
   geom_point(size = 2) +
   labs(title = "{closest_state}") +
@@ -282,14 +282,14 @@ ggplot(iris, aes(Petal.Length, Sepal.Length)) +
 ```
 
 ### shadow_trail()
-```{r ggplot2-gganimate-19}
+```{r ggplot2-gganimate-19, eval=FALSE}
 p +
   transition_time(time = year) +
   labs(title = "year: {frame_time}") +
   shadow_trail(distance = 0.1)
 ```
 
-```{r ggplot2-gganimate-20}
+```{r ggplot2-gganimate-20, eval=FALSE}
 ggplot(iris, aes(Petal.Length, Sepal.Length)) +
   geom_point(size = 2) +
   labs(title = "{closest_state}") +
@@ -300,15 +300,15 @@ ggplot(iris, aes(Petal.Length, Sepal.Length)) +
 
 ### shadow_mark()
 
-```{r ggplot2-gganimate-21}
+```{r ggplot2-gganimate-21, eval=FALSE}
 p +
   transition_time(time = year) +
   labs(title = "year: {frame_time}") +
   shadow_mark(alpha = 0.3, size = 0.5)
 ```
 
 
-```{r ggplot2-gganimate-22}
+```{r ggplot2-gganimate-22, eval=FALSE}
 ggplot(airquality, aes(Day, Temp)) +
   geom_line(color = "red", size = 1) +
   transition_time(Month) +
@@ -321,7 +321,7 @@ ggplot(airquality, aes(Day, Temp)) +
 
 出现和退去的函数是成对的
 
-```{r enter-exit-tbl, echo=FALSE}
+```{r enter-exit-tbl, echo=FALSE, eval=FALSE}
 tribble(
   ~Function, ~Description,
   "enter_appear/exit_disappear", "突然出现，或者闪退",
@@ -338,7 +338,7 @@ tribble(
 
 透明度上的变化，我这里用柱状图展示，效果要明显一点。
 
-```{r ggplot2-gganimate-23}
+```{r ggplot2-gganimate-23, eval=FALSE}
 tibble(
   x = month.name,
   y = sample.int(12)
@@ -350,7 +350,7 @@ tibble(
 ```
 
 
-```{r ggplot2-gganimate-24}
+```{r ggplot2-gganimate-24, eval=FALSE}
 tibble(
   x = month.name,
   y = sample.int(12)
@@ -364,7 +364,7 @@ tibble(
 ```
 
 
-```{r ggplot2-gganimate-25}
+```{r ggplot2-gganimate-25, eval=FALSE}
 p +
   transition_time(time = year) +
   labs(title = "year: {frame_time}") +
@@ -375,7 +375,7 @@ p +
 
 大小上的变化
 
-```{r ggplot2-gganimate-26}
+```{r ggplot2-gganimate-26, eval=FALSE}
 tibble(
   x = month.name,
   y = sample.int(12)
@@ -389,7 +389,7 @@ tibble(
 ```
 
 
-```{r ggplot2-gganimate-27}
+```{r ggplot2-gganimate-27, eval=FALSE}
 p +
   transition_time(time = year) +
   labs(title = "year: {frame_time}") +
@@ -418,15 +418,15 @@ Source: https://easings.net/
 
 
 看下面的案例：
-```{r ggplot2-gganimate-29}
+```{r ggplot2-gganimate-29, eval=FALSE}
 diamonds %>%
   ggplot(aes(carat, price)) +
   geom_point() +
   transition_states(color, transition_length = 3, state_length = 1) +
   ease_aes("cubic-in") # Change easing of all aesthetics
 ```
 
-```{r ggplot2-gganimate-30}
+```{r ggplot2-gganimate-30, eval=FALSE}
 diamonds %>%
   ggplot(aes(carat, price)) +
   geom_point() +
@@ -558,7 +558,7 @@ anim_save("first_saved_animation.gif", animation = animation_to_save)
 
 这是网上有段时间比较火的racing_bar图
 
-```{r ggplot2-gganimate-33}
+```{r ggplot2-gganimate-33, eval=FALSE}
 ranked_by_date <- covdata::covnat %>%
   group_by(date) %>%
   arrange(date, desc(cu_cases)) %>%
@@ -568,7 +568,7 @@ ranked_by_date <- covdata::covnat %>%
 ```
 
 
-```{r ggplot2-gganimate-34}
+```{r ggplot2-gganimate-34, eval=FALSE}
 ranked_by_date %>%
   filter(date >= "2020-05-01") %>%
   ggplot(
@@ -611,14 +611,14 @@ ranked_by_date %>%
 
 ## 案例演示二
 
-```{r ggplot2-gganimate-35}
+```{r ggplot2-gganimate-35, eval=FALSE}
 bats <- readr::read_csv("./demo_data/bats-subset.csv") %>%
   dplyr::mutate(id = factor(id))
 ```
 
 
 
-```{r ggplot2-gganimate-36}
+```{r ggplot2-gganimate-36, eval=FALSE}
 bats %>%
   ggplot(aes(
     x = longitude,
@@ -634,7 +634,7 @@ bats %>%
 
 ### 常规的方法
 
-```{r ggplot2-gganimate-37}
+```{r ggplot2-gganimate-37, eval=FALSE}
 bats %>%
   ggplot(aes(
     x = longitude,
@@ -652,7 +652,7 @@ bats %>%
 - geom_path()是按照数据点出现的先后顺序
 - geom_line()是按照数据点在x轴的顺序
 
-```{r ggplot2-gganimate-38}
+```{r ggplot2-gganimate-38, eval=FALSE}
 bats %>%
   ggplot(aes(
     x = longitude,
@@ -671,7 +671,7 @@ bats %>%
 <!-- 此时geom_path() + transition_reveal(time) = transition_time(time) -->
 
 
-```{r ggplot2-gganimate-39}
+```{r ggplot2-gganimate-39, eval=FALSE}
 bats %>%
   dplyr::mutate(
     image = "images/bat-cartoon.png"
@@ -691,7 +691,7 @@ bats %>%
 ## 案例演示三
 
 全球R-Ladies组织，会议活动的情况，我们在地图上用动图展示
-```{r ggplot2-gganimate-40}
+```{r ggplot2-gganimate-40, eval=FALSE}
 rladies <- read_csv("./demo_data/rladies.csv")
 rladies
 ```
@@ -835,7 +835,7 @@ bats %>%
 # remove the objects
 # rm(list=ls())
 #rm(anim, bats, p, ranked_by_date, rladies, world, world_map)
-rm(anim, bats, p, ranked_by_date, rladies)
+#rm(anim, bats, p, ranked_by_date, rladies)
 ```
 
 

index.Rmd

@@ -25,7 +25,7 @@ options(
   htmltools.dir.version = FALSE, formatR.indent = 2, width = 55, digits = 4
 )
 
-knitr::opts_chunk$set(cache = TRUE,
+knitr::opts_chunk$set(
                       echo = TRUE, 
                       warning = FALSE, 
                       message = FALSE,