R语言gganimate疫情数据动态可视化

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R语言gganimate学习
所需加载包
library(av)
! k7 F6 x8 R8 V" e4 dlibrary(ggplot2)
library(gganimate)
library(tidyverse)
9 x3 S4 i3 p$ B7 z4 ?' I8 {library(lubridate)
library(scales)
& @6 F7 o4 B% glibrary(ggrepel)
  c9 T! I; B5 ^  ]/ |6 m3 a9 dlibrary(cowplot)
数据


# {$ f% b# ?+ n: nps = ggplot(mydatan, aes(x=reorder(省份, 累计确诊),y=累计确诊, fill=省份,frame=Date)) +
     geom_bar(stat= 'identity', position = 'dodge',show.legend = FALSE) +
7 `' b- X$ h5 _0 g% y/ k    geom_text(aes(label=paste0(累计确诊)),col="black",hjust=-0.2)+
) o" c( u% y0 J    #theme_bw()+
   #theme(legend.position="none") +
    theme(axis.text.x = element_text(size = 12,angle = 90, hjust = 0.2, vjust = 0.2),legend.position="none") +
    theme(panel.background=element_rect(fill='transparent'))+
; p% V# D/ G6 |- b& l+ U7 R  theme(axis.text.y=element_text(angle=0,colour="black",size=12,hjust=1))+
  theme(axis.text.x=element_text(angle=0,colour="white",size=2,hjust=1))+
   theme(panel.grid =element_blank()) +   ## 删去网格线
; u$ q) x# u, L3 b# D5 ?& `% Q, a  theme(axis.text = element_blank()) +   ## 删去所有刻度标签
* C8 H( X  _% j: M8 M5 X1 L  theme(axis.ticks = element_blank()) +  ## 删去所有刻度线
5 B# b6 q( g. L& k3 \% ^# Here comes the gganimate specific bits
# Y4 z8 ~# [3 F; T3 S" b#labs(title = '日期:', x = '省份', y = '累计确诊病例') +
#annotate("text",x=0,y=40,label=C,parse=T)+
  ^2 ^# r8 |9 T+ O4 [) Xcoord_flip()+
transition_manual(frames=as.Date(Date)) +
#ggdark::dark_theme_bw() + #设置黑色主题
labs(title = paste('日期:', '{current_frame}'),x = '', y ='各省累计确诊病例增长(除湖北省外)')+
# R& H8 \9 i. B1 aease_aes('linear')
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结果展示
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视频格式转化，加载BGM
#df <- animate(ps, renderer = av_renderer('animation.mp4'),
  }* t  `& [" ~5 c  X0 m1 v         #     width = 1280, height = 720, res = 100, fps = 10)#视频制作
# av_encode_video(df, 'output.mp4', framerate = 2,audio ="N.mp3")
4 {& A8 y8 W" p2 v( J# H9 j/ ~全国新冠状肺炎26天增长状况
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) g4 k1 }. |" O) P# E7 U, O* E& ipc<-ggplot(data=CNdata_s,aes(x=variable,y=value,fill=variable,frame=Date))+
   geom_bar(stat= 'identity', position = 'dodge',show.legend = FALSE,width=0.7) +
. X& i3 @$ b  W' P% e* S8 S1 b   geom_text(aes(label=paste0(value)),col="black",hjust=-0.2)+
/ C" I8 n- W5 o6 Q0 g    theme(legend.position="none") +
  theme(panel.background=element_rect(fill='transparent'))+
  theme(axis.text.x=element_text(angle=0,colour="black",size=15,hjust=1))+
  theme(axis.text.y=element_text(angle=0,colour="white",size=2,hjust=1))+
* D' s0 g8 K) O' ~/ _# V7 W   theme(panel.grid =element_blank()) +   ## 删去网格线
  theme(axis.text = element_blank()) +   ## 删去所有刻度标签
  theme(axis.ticks = element_blank()) +  ## 删去所有刻度线
4 U- f# T: a2 R; i: Y3 L8 @  #scale_x_continuous(limits = c(0,6))+
# Here comes the gganimate specific bits
8 p# r, D# U( ^/ V: w: y- e) ]- M#labs(title = '日期:', x = '省份', y = '累计确诊病例') +
  E" {# N3 E, L; k# V#annotate("text",x=0,y=40,label=C,parse=T)+
6 r* F- e) J& c8 H7 G+ V5 K9 t    # coord_flip()+
     transition_manual(frames=as.Date(Date)) +
    # ggdark::dark_theme_bw() + #设置黑色主题
     labs(title = paste('日期:', '{current_frame}'),x = '全国新冠状肺炎增长', y ='')+
# O' f6 x5 H# T, I# y     ease_aes('linear')
pc

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动态图合并
. C8 ~+ [) |* J, F  Ilibrary(magick)
ps_gif <- animate(ps,,width = 720, height = 480)
pc_gif <- animate(pc, width = 360, height = 480)
ps_gifs <- image_read(ps_gif)
pc_gifs <- image_read(pc_gif)
- K. F4 a, m+ Y8 D* F7 Onew_gif <- image_append(c(pc_gifs[1], ps_gifs[1]))
for(i in 2:length(pc_gifs)){
  combined <- image_append(c(pc_gifs, ps_gifs))
  new_gif <- c(new_gif, combined)
8 q- l. B' W, A+ a}
new_gif
结果展示
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