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
/ O4 P3 Q5 O. Llibrary(av)
library(ggplot2)
library(gganimate)
+ M; A1 G+ R: M+ S& N& v2 q  wlibrary(tidyverse)
" ~1 t0 ?0 c' alibrary(lubridate)
library(scales)
' Z! |% ?* _7 K2 H$ ?library(ggrepel)
library(cowplot)
数据
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! X" c! T2 J- Aps = 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") +
    theme(axis.text.x = element_text(size = 12,angle = 90, hjust = 0.2, vjust = 0.2),legend.position="none") +
! I( `- s$ k8 ?: w7 s7 p    theme(panel.background=element_rect(fill='transparent'))+
; p7 b5 {0 m3 F- K+ |  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
  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 B# Z+ g6 n& ^( Q7 @- y4 n1 y# Here comes the gganimate specific bits
#labs(title = '日期:', x = '省份', y = '累计确诊病例') +
. `' C7 [# Z! V- N1 n#annotate("text",x=0,y=40,label=C,parse=T)+
  w2 ?  Y+ ^) C; m% qcoord_flip()+
0 S6 E3 S4 w* o4 {6 t; y: ttransition_manual(frames=as.Date(Date)) +
! U' B/ i& t, `2 `#ggdark::dark_theme_bw() + #设置黑色主题
" ?. }! ]3 q$ P- M) Ylabs(title = paste('日期:', '{current_frame}'),x = '', y ='各省累计确诊病例增长(除湖北省外)')+
2 g1 S( f7 u1 e5 N! W) {$ Dease_aes('linear')
ps
6 u+ R6 V" o9 `' |% M# B结果展示


8 g2 Y1 ~" p' n5 T0 b6 F视频格式转化，加载BGM
#df <- animate(ps, renderer = av_renderer('animation.mp4'),
         #     width = 1280, height = 720, res = 100, fps = 10)#视频制作
! a8 {4 k# Z& x5 h; R5 c, H! h# av_encode_video(df, 'output.mp4', framerate = 2,audio ="N.mp3")
1 B$ I" }# P1 i8 L2 P7 Z4 D全国新冠状肺炎26天增长状况

( g% O- X7 w) L: c2 Fpc<-ggplot(data=CNdata_s,aes(x=variable,y=value,fill=variable,frame=Date))+
$ h" E% I2 Y9 t# s& H   geom_bar(stat= 'identity', position = 'dodge',show.legend = FALSE,width=0.7) +
   geom_text(aes(label=paste0(value)),col="black",hjust=-0.2)+
    theme(legend.position="none") +
! h" C& ~$ ?* t( S  Y% c! M  theme(panel.background=element_rect(fill='transparent'))+
  theme(axis.text.x=element_text(angle=0,colour="black",size=15,hjust=1))+
0 u2 |- L% Y* M! V, w  theme(axis.text.y=element_text(angle=0,colour="white",size=2,hjust=1))+
   theme(panel.grid =element_blank()) +   ## 删去网格线
3 W# K7 @4 P, W- `  I; ]  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))+
# 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()+
- X0 f, W* e8 Y. h     transition_manual(frames=as.Date(Date)) +
1 B( ^: B' E9 g    # ggdark::dark_theme_bw() + #设置黑色主题
6 m0 `. h8 [! D8 D     labs(title = paste('日期:', '{current_frame}'),x = '全国新冠状肺炎增长', y ='')+
     ease_aes('linear')
pc
6 W3 |5 f9 O' V- W% ?9 }+ N

4 ?- r& l5 s* k9 C" ~9 q动态图合并
, o5 q# ], r; t% L' N" Blibrary(magick)
ps_gif <- animate(ps,,width = 720, height = 480)
pc_gif <- animate(pc, width = 360, height = 480)
! f5 d% ~6 o: I9 E+ R8 L4 Q! pps_gifs <- image_read(ps_gif)
pc_gifs <- image_read(pc_gif)
8 F$ d- z* d" _3 e9 znew_gif <- image_append(c(pc_gifs[1], ps_gifs[1]))
3 V. G+ P2 ?/ O4 l! Cfor(i in 2:length(pc_gifs)){
8 P( P" t' c; `; O, G+ j* s' \  combined <- image_append(c(pc_gifs, ps_gifs))
  new_gif <- c(new_gif, combined)
}
new_gif
3 o" B3 r! M6 N' C8 }结果展示

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