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
; K2 ^7 `: B, ~- X+ Y- K! nlibrary(av)
library(ggplot2)
library(gganimate)
0 g5 j& B- p& L7 ^( t7 ]3 Llibrary(tidyverse)
library(lubridate)
library(scales)
library(ggrepel)
library(cowplot)
5 t% Z3 a* x/ i: \0 d数据

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ps = 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) +
    geom_text(aes(label=paste0(累计确诊)),col="black",hjust=-0.2)+
    #theme_bw()+
   #theme(legend.position="none") +
$ q' t; M9 d2 {& `2 K    theme(axis.text.x = element_text(size = 12,angle = 90, hjust = 0.2, vjust = 0.2),legend.position="none") +
" a. L* M- c1 j6 {    theme(panel.background=element_rect(fill='transparent'))+
  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))+
) x$ Q2 f" [# k+ U   theme(panel.grid =element_blank()) +   ## 删去网格线
, F6 m! K! W0 Q8 Z  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
# Here comes the gganimate specific bits
#labs(title = '日期:', x = '省份', y = '累计确诊病例') +
- t4 ?2 U9 p) J1 h$ k$ l#annotate("text",x=0,y=40,label=C,parse=T)+
, o/ i8 W1 O# n4 t; _; e& Fcoord_flip()+
transition_manual(frames=as.Date(Date)) +
' ?; N4 u+ j8 n$ G1 @#ggdark::dark_theme_bw() + #设置黑色主题
1 E' t1 e5 |* J( D1 W3 u) R( h. _. Blabs(title = paste('日期:', '{current_frame}'),x = '', y ='各省累计确诊病例增长(除湖北省外)')+
4 b2 ~6 K, ^9 A/ ^' E- Bease_aes('linear')
ps
# }. b6 [  u& g% Z8 h( f( x3 @结果展示
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视频格式转化，加载BGM
' }$ m, K6 J+ F1 |* f! a#df <- animate(ps, renderer = av_renderer('animation.mp4'),
: K2 d$ S9 z" n7 m+ r         #     width = 1280, height = 720, res = 100, fps = 10)#视频制作
; y' P2 N3 d  p0 H# av_encode_video(df, 'output.mp4', framerate = 2,audio ="N.mp3")
全国新冠状肺炎26天增长状况

: F! h" @7 T: X$ L/ Dpc<-ggplot(data=CNdata_s,aes(x=variable,y=value,fill=variable,frame=Date))+
2 f# ~% K+ q8 ?4 j  U! I% ^1 [& a   geom_bar(stat= 'identity', position = 'dodge',show.legend = FALSE,width=0.7) +
# A" v3 v7 w$ ^" y' h( g   geom_text(aes(label=paste0(value)),col="black",hjust=-0.2)+
    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))+
   theme(panel.grid =element_blank()) +   ## 删去网格线
1 Y) B) N  Y( {# l+ H" f  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
1 A8 F6 X% |& \* q  #scale_x_continuous(limits = c(0,6))+
# Here comes the gganimate specific bits
+ F( C, v. t  I, W/ ~+ |# x#labs(title = '日期:', x = '省份', y = '累计确诊病例') +
- n# o9 h) M' O* z6 K- W#annotate("text",x=0,y=40,label=C,parse=T)+
    # coord_flip()+
. d- s5 z0 A' D% @- U0 q9 {     transition_manual(frames=as.Date(Date)) +
* y( m/ b5 T& f7 c! I" p: h# }    # 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 ='')+
     ease_aes('linear')
pc

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动态图合并
library(magick)
1 P2 f0 a/ Y$ c  lps_gif <- animate(ps,,width = 720, height = 480)
2 T7 B) {8 L$ l& opc_gif <- animate(pc, width = 360, height = 480)
+ w9 s* f" x. Y8 H8 I9 Z: y7 n: tps_gifs <- image_read(ps_gif)
# h, \1 m5 m9 h( N% e4 ?  X3 Spc_gifs <- image_read(pc_gif)
7 T% P0 |3 V  g8 ^! ~  ?6 u. snew_gif <- image_append(c(pc_gifs[1], ps_gifs[1]))
" u9 r3 a+ T3 ]1 ]4 |for(i in 2:length(pc_gifs)){
$ Q8 P. n5 K/ Y. ~/ z8 U6 B+ r  combined <- image_append(c(pc_gifs, ps_gifs))
$ D0 c9 @$ g4 |* ]; v0 v! L  new_gif <- c(new_gif, combined)
' t$ U9 l6 W1 }$ J, |& }}
' g% ~1 y+ [- l; T# \new_gif
9 w- T$ K4 u, I  }结果展示
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