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
library(av)
library(ggplot2)
1 \' f; v4 ]5 v0 V7 f5 _" Z( G+ r5 Ulibrary(gganimate)
$ g8 a' o& e9 Wlibrary(tidyverse)
  t  H" H4 W: z& R8 k3 glibrary(lubridate)
; s4 A! k+ r! _4 r. Zlibrary(scales)
% M% S5 @8 k6 i8 u- p$ clibrary(ggrepel)
library(cowplot)
数据


! E; H- ]6 w/ V" c" u! ips = 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) +
% V+ R" S" e' j( v% x    geom_text(aes(label=paste0(累计确诊)),col="black",hjust=-0.2)+
    #theme_bw()+
1 S* k4 i  h) A2 J   #theme(legend.position="none") +
0 h  e$ C# g# x7 s( H" ]1 E3 X2 l    theme(axis.text.x = element_text(size = 12,angle = 90, hjust = 0.2, vjust = 0.2),legend.position="none") +
7 M' O; q1 E4 U1 \* I' m    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))+
! a. V) ?+ E3 m9 ~/ x   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
( X$ O8 x- y0 c0 t#labs(title = '日期:', x = '省份', y = '累计确诊病例') +
2 z  C" [8 |2 C#annotate("text",x=0,y=40,label=C,parse=T)+
$ F) \; f  }( P8 v/ ~" r7 N3 qcoord_flip()+
transition_manual(frames=as.Date(Date)) +
# q* K: S8 a3 B+ L3 ?5 Q' d9 X& {#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)')+
% {1 k5 k$ r3 _0 n' {' Eease_aes('linear')
  g( g- V( q) V4 C% Kps
' Q+ h' i* {8 k# G5 B结果展示


视频格式转化，加载BGM
#df <- animate(ps, renderer = av_renderer('animation.mp4'),
* r: h$ o& i8 H         #     width = 1280, height = 720, res = 100, fps = 10)#视频制作
, ]# C  `' H% n9 Q$ y# av_encode_video(df, 'output.mp4', framerate = 2,audio ="N.mp3")
/ O( G7 G- P# q; Q全国新冠状肺炎26天增长状况
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6 Z! b, N+ V. O& k) l! wpc<-ggplot(data=CNdata_s,aes(x=variable,y=value,fill=variable,frame=Date))+
; n  z7 y2 \4 `" S7 I   geom_bar(stat= 'identity', position = 'dodge',show.legend = FALSE,width=0.7) +
   geom_text(aes(label=paste0(value)),col="black",hjust=-0.2)+
8 Y' ~7 H6 i" I& S6 M% i    theme(legend.position="none") +
  theme(panel.background=element_rect(fill='transparent'))+
: U& C7 w/ `/ v/ S. ], v* e& G  theme(axis.text.x=element_text(angle=0,colour="black",size=15,hjust=1))+
+ R% R/ U* C, o6 z/ O$ ^  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. U5 d& R" L1 s" g$ }  theme(axis.ticks = element_blank()) +  ## 删去所有刻度线
* D. z5 [& ]8 s& q" J* n0 W  #scale_x_continuous(limits = c(0,6))+
# Here comes the gganimate specific bits
! P5 Z& O& [1 L: p) K# B& p#labs(title = '日期:', x = '省份', y = '累计确诊病例') +
, F+ Y4 s( r: q' |3 K! `# ^. ?+ s0 C#annotate("text",x=0,y=40,label=C,parse=T)+
& y0 O4 S5 A& M$ _    # coord_flip()+
     transition_manual(frames=as.Date(Date)) +
/ [( X$ P( D' z" E" g    # ggdark::dark_theme_bw() + #设置黑色主题
& f/ L6 ~! v  m. X1 A- W( g     labs(title = paste('日期:', '{current_frame}'),x = '全国新冠状肺炎增长', y ='')+
. T5 J! _3 Z. ], X     ease_aes('linear')
pc

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动态图合并
  u1 R8 r9 j4 z# O& ]& nlibrary(magick)
' f3 M# A' ~  H8 tps_gif <- animate(ps,,width = 720, height = 480)
pc_gif <- animate(pc, width = 360, height = 480)
6 v7 J5 [& X# |; \ps_gifs <- image_read(ps_gif)
pc_gifs <- image_read(pc_gif)
$ y! K( q7 m5 T" M6 hnew_gif <- image_append(c(pc_gifs[1], ps_gifs[1]))
$ a! H) H2 U6 W8 Hfor(i in 2:length(pc_gifs)){
  combined <- image_append(c(pc_gifs, ps_gifs))
  new_gif <- c(new_gif, combined)
6 s1 l6 c3 S: Q2 `! q5 W}
$ z, ?7 x% d  I: `new_gif
4 A. |& f1 V" g6 W结果展示
) u( C* _5 ~3 f5 {2 t* S
% z5 c' Q  q. j: _  F) s
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