R语言gganimate疫情数据动态可视化

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R语言gganimate学习
  o$ H! S& E- N9 x7 ?, g- U所需加载包
& N+ @  v7 x" R3 vlibrary(av)
  n2 G, L' t4 y# ~) ulibrary(ggplot2)
7 z8 V; X8 x( [, Tlibrary(gganimate)
! |( G( S) \" ulibrary(tidyverse)
library(lubridate)
library(scales)
library(ggrepel)
8 w$ q9 H& V- klibrary(cowplot)
数据


* o& m- J8 t) b4 |- g. l$ f: sps = ggplot(mydatan, aes(x=reorder(省份, 累计确诊),y=累计确诊, fill=省份,frame=Date)) +
- b# F, U2 G& _# e1 f     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") +
    theme(panel.background=element_rect(fill='transparent'))+
. e  u) R, |' i+ x0 o8 h. ^( t  theme(axis.text.y=element_text(angle=0,colour="black",size=12,hjust=1))+
& F1 ?6 z2 C1 A) d8 e0 b* P  theme(axis.text.x=element_text(angle=0,colour="white",size=2,hjust=1))+
; o: j9 p# e- U   theme(panel.grid =element_blank()) +   ## 删去网格线
# ]$ v9 H0 m9 L$ b' \  theme(axis.text = element_blank()) +   ## 删去所有刻度标签
) b  U  H' k: b  theme(axis.ticks = element_blank()) +  ## 删去所有刻度线
# Here comes the gganimate specific bits
& [7 Z6 K. j, }0 M0 u#labs(title = '日期:', x = '省份', y = '累计确诊病例') +
: U, D6 c4 a. \( k4 B, L& ]1 [#annotate("text",x=0,y=40,label=C,parse=T)+
5 p2 B' N2 L, N, L6 W) G7 O$ m! A( scoord_flip()+
transition_manual(frames=as.Date(Date)) +
7 @; E3 w9 f2 L+ Y% ~3 Y#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
6 x9 N- g7 E5 [7 p3 K# L结果展示


视频格式转化，加载BGM
3 l* i6 q7 o( l4 v1 G4 I4 X/ ]#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")
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))+
   geom_bar(stat= 'identity', position = 'dodge',show.legend = FALSE,width=0.7) +
- D; e7 v6 E/ s4 k4 N, _   geom_text(aes(label=paste0(value)),col="black",hjust=-0.2)+
    theme(legend.position="none") +
0 U% y4 L3 p5 y, _+ J% j  theme(panel.background=element_rect(fill='transparent'))+
0 Y5 x) V* l/ Y' G6 V5 V; ]7 I  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
4 b, M0 ], [" r  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
) `) m8 n+ L* D: d% z* |  W#labs(title = '日期:', x = '省份', y = '累计确诊病例') +
7 m6 L2 u7 e3 f# ~% Y5 ?3 O3 P4 H#annotate("text",x=0,y=40,label=C,parse=T)+
4 J0 d8 g' U  N2 x    # coord_flip()+
5 B/ B1 e: {  q7 b4 ^     transition_manual(frames=as.Date(Date)) +
0 o2 X3 m/ R! S6 C1 z    # 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
7 S9 C1 N- x9 q) C

动态图合并
library(magick)
ps_gif <- animate(ps,,width = 720, height = 480)
pc_gif <- animate(pc, width = 360, height = 480)
ps_gifs <- image_read(ps_gif)
( I. d( y. t9 G  o1 M5 u1 spc_gifs <- image_read(pc_gif)
new_gif <- image_append(c(pc_gifs[1], ps_gifs[1]))
for(i in 2:length(pc_gifs)){
( H  r* q. ?* X) O  combined <- image_append(c(pc_gifs, ps_gifs))
( M' T, x; S9 u8 B" T# E8 }  new_gif <- c(new_gif, combined)
}
9 P' Q( I' Z7 a+ D( hnew_gif
# Z$ r  R, {( ^! s# C结果展示
& i5 n9 y2 T3 @- A+ A1 P# X9 p, v. A

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