R语言gganimate疫情数据动态可视化

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R语言gganimate学习
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library(av)
% i0 w9 [: O/ }) c: p; Blibrary(ggplot2)
library(gganimate)
library(tidyverse)
/ ~$ t0 K$ L, X2 \library(lubridate)
1 l. |- n0 H! ?library(scales)
library(ggrepel)
' j! r; S, ~% V6 zlibrary(cowplot)
% P7 i9 ]" c( }数据

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% q5 h) o" U% o/ wps = ggplot(mydatan, aes(x=reorder(省份, 累计确诊),y=累计确诊, fill=省份,frame=Date)) +
7 a# P6 F5 u* @* z) S9 l% _  Z& O     geom_bar(stat= 'identity', position = 'dodge',show.legend = FALSE) +
' G1 |+ q( H; V; i2 m& ~( C    geom_text(aes(label=paste0(累计确诊)),col="black",hjust=-0.2)+
    #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") +
: v* Q5 o* i# a  ]# @    theme(panel.background=element_rect(fill='transparent'))+
  theme(axis.text.y=element_text(angle=0,colour="black",size=12,hjust=1))+
9 R# ~: d. M9 f' t% o/ B  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
# 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)+
coord_flip()+
$ p$ k# j, n/ w/ L  W3 u4 @4 w3 Ktransition_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)')+
ease_aes('linear')
ps
7 Q) w, b2 q9 R$ u, Q* i结果展示
+ z! w* `# e6 O

视频格式转化，加载BGM
#df <- animate(ps, renderer = av_renderer('animation.mp4'),
; L  `6 A6 [- ?% l6 ^' n5 P         #     width = 1280, height = 720, res = 100, fps = 10)#视频制作
/ b2 m* I1 |2 p6 e2 D# av_encode_video(df, 'output.mp4', framerate = 2,audio ="N.mp3")
全国新冠状肺炎26天增长状况

pc<-ggplot(data=CNdata_s,aes(x=variable,y=value,fill=variable,frame=Date))+
% a* B/ J/ x7 i# n5 i   geom_bar(stat= 'identity', position = 'dodge',show.legend = FALSE,width=0.7) +
   geom_text(aes(label=paste0(value)),col="black",hjust=-0.2)+
. X. t0 K' o6 l) @$ B" N1 _* g    theme(legend.position="none") +
6 p+ Z. Y" ?0 {" \0 O# Z! C' z  theme(panel.background=element_rect(fill='transparent'))+
5 |9 Z) @7 O6 R; ?  W  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
' @  s3 k) c. T( u5 u: `  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
  #scale_x_continuous(limits = c(0,6))+
! s7 L5 y0 k4 A0 L4 E # 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)+
    # coord_flip()+
     transition_manual(frames=as.Date(Date)) +
    # ggdark::dark_theme_bw() + #设置黑色主题
- B% t0 T6 M" Z     labs(title = paste('日期:', '{current_frame}'),x = '全国新冠状肺炎增长', y ='')+
, b8 w. o3 _- ?4 R3 W2 J1 o7 N     ease_aes('linear')
/ M; Q- N9 k0 l8 X# Hpc
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& A  _* w/ V  ]+ g7 I; ^动态图合并
0 f+ m1 f, Y5 Rlibrary(magick)
ps_gif <- animate(ps,,width = 720, height = 480)
  l! F" b3 T- q& d8 }$ Kpc_gif <- animate(pc, width = 360, height = 480)
  Z' K5 g) J. O* j3 X# h9 B# c) {ps_gifs <- image_read(ps_gif)
7 q& ~1 X3 w) w% ?, ]7 r5 D* Y. Opc_gifs <- image_read(pc_gif)
new_gif <- image_append(c(pc_gifs[1], ps_gifs[1]))
2 M) E" M" h/ N& m; jfor(i in 2:length(pc_gifs)){
' [  }8 r) ]# h! w8 _7 o  combined <- image_append(c(pc_gifs, ps_gifs))
  new_gif <- c(new_gif, combined)
}
new_gif
结果展示
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