R语言gganimate疫情数据动态可视化

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R语言gganimate学习
# x# ?4 C. o8 Y! s: t. J/ n0 u所需加载包
' V9 J, R( s& k0 a: K. Alibrary(av)
library(ggplot2)
& n' `( t" D% k, R& ]library(gganimate)
" Z" J, m1 R  @2 c3 Q* a8 Q& xlibrary(tidyverse)
library(lubridate)
library(scales)
library(ggrepel)
$ M0 ^$ J" ?+ |0 ~& I. T8 e! ?library(cowplot)
数据


) q( |( h0 e; [- a- A+ w8 Sps = ggplot(mydatan, aes(x=reorder(省份, 累计确诊),y=累计确诊, fill=省份,frame=Date)) +
; l, Z. k6 }. k' d) y/ [) V     geom_bar(stat= 'identity', position = 'dodge',show.legend = FALSE) +
    geom_text(aes(label=paste0(累计确诊)),col="black",hjust=-0.2)+
    #theme_bw()+
   #theme(legend.position="none") +
9 y8 s' D. b+ v3 m/ ?" C0 R1 }) o    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'))+
" k7 h/ c8 `; p6 F2 c  theme(axis.text.y=element_text(angle=0,colour="black",size=12,hjust=1))+
1 _* V" E( w% h  theme(axis.text.x=element_text(angle=0,colour="white",size=2,hjust=1))+
   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
7 `8 ?& U) y1 R, q/ A* i4 U" n# Here comes the gganimate specific bits
#labs(title = '日期:', x = '省份', y = '累计确诊病例') +
$ @+ M( n7 ~8 P& @1 H5 I3 I& `#annotate("text",x=0,y=40,label=C,parse=T)+
4 S0 t; v$ ~3 |! `* a; `' r2 @coord_flip()+
# x+ f3 R* x) \* j8 Mtransition_manual(frames=as.Date(Date)) +
$ C2 @+ B" b9 L5 N#ggdark::dark_theme_bw() + #设置黑色主题
4 O- c6 C5 \& I3 blabs(title = paste('日期:', '{current_frame}'),x = '', y ='各省累计确诊病例增长(除湖北省外)')+
3 i- |: U0 ^9 {. F/ Q% oease_aes('linear')
ps
3 o( [! H: M/ W' f2 B* Y9 I! ]. Q结果展示
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8 y& d- [7 N! `; @视频格式转化，加载BGM
7 @% H5 Z  l' N! J#df <- animate(ps, renderer = av_renderer('animation.mp4'),
         #     width = 1280, height = 720, res = 100, fps = 10)#视频制作
# av_encode_video(df, 'output.mp4', framerate = 2,audio ="N.mp3")
$ z  l& h" d4 d. d7 i全国新冠状肺炎26天增长状况
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pc<-ggplot(data=CNdata_s,aes(x=variable,y=value,fill=variable,frame=Date))+
. y- w+ q7 q) D   geom_bar(stat= 'identity', position = 'dodge',show.legend = FALSE,width=0.7) +
. @3 v: y" n# a) e! ?0 x7 j( I* l   geom_text(aes(label=paste0(value)),col="black",hjust=-0.2)+
8 }, D6 S( H2 Z6 v: k4 q    theme(legend.position="none") +
1 Q1 l. A: r; c5 D% P  theme(panel.background=element_rect(fill='transparent'))+
' h# Y6 A' w3 I- @; Y" D4 z2 [  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))+
   theme(panel.grid =element_blank()) +   ## 删去网格线
  theme(axis.text = element_blank()) +   ## 删去所有刻度标签
" D; c& C9 n" t7 A1 Y  theme(axis.ticks = element_blank()) +  ## 删去所有刻度线
" m3 v; T9 }2 C& V6 K* y  #scale_x_continuous(limits = c(0,6))+
# Here comes the gganimate specific bits
#labs(title = '日期:', x = '省份', y = '累计确诊病例') +
#annotate("text",x=0,y=40,label=C,parse=T)+
  P" c. L! X0 f$ C    # coord_flip()+
" p" O/ A% x) J: e* z7 G     transition_manual(frames=as.Date(Date)) +
& z) y7 W# {% B    # ggdark::dark_theme_bw() + #设置黑色主题
# @6 g1 h3 j# W# {- c! }     labs(title = paste('日期:', '{current_frame}'),x = '全国新冠状肺炎增长', y ='')+
     ease_aes('linear')
pc
' I8 S4 E; u9 m4 r2 R

动态图合并
. x8 ~- @* Z) g+ r+ s2 b1 U) Flibrary(magick)
ps_gif <- animate(ps,,width = 720, height = 480)
pc_gif <- animate(pc, width = 360, height = 480)
ps_gifs <- image_read(ps_gif)
! T3 S; ~9 c. R- T9 Epc_gifs <- image_read(pc_gif)
1 J7 z6 t  y; ]; Y3 i- \7 J: E( L6 qnew_gif <- image_append(c(pc_gifs[1], ps_gifs[1]))
5 X: e* z! W  p0 }: Pfor(i in 2:length(pc_gifs)){
  combined <- image_append(c(pc_gifs, ps_gifs))
6 O4 n: M" m  _# L  new_gif <- c(new_gif, combined)
8 |, d5 [5 Y* q}
new_gif
结果展示
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