R语言gganimate疫情数据动态可视化

1047521767

R语言gganimate学习
所需加载包
library(av)
- D* E7 C9 f4 s+ Xlibrary(ggplot2)
% N2 C3 J4 L. zlibrary(gganimate)
library(tidyverse)
library(lubridate)
) }# g$ ?& `: o  Flibrary(scales)
% q/ `9 @0 q; O# |3 alibrary(ggrepel)
8 h  M* q: J" g) S# G( [" Q* mlibrary(cowplot)
( {3 f5 N" n3 {( ]数据
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/ L9 P3 l' h8 r* N3 ~ps = ggplot(mydatan, aes(x=reorder(省份, 累计确诊),y=累计确诊, fill=省份,frame=Date)) +
5 d# X7 M# h; D$ p# _9 u     geom_bar(stat= 'identity', position = 'dodge',show.legend = FALSE) +
6 }* Q, Q9 M1 @6 D    geom_text(aes(label=paste0(累计确诊)),col="black",hjust=-0.2)+
    #theme_bw()+
" H/ |: D) i  g8 ^4 p. K   #theme(legend.position="none") +
! H+ d+ u- t' p6 R    theme(axis.text.x = element_text(size = 12,angle = 90, hjust = 0.2, vjust = 0.2),legend.position="none") +
. F/ M" E6 f0 x" f9 f    theme(panel.background=element_rect(fill='transparent'))+
  theme(axis.text.y=element_text(angle=0,colour="black",size=12,hjust=1))+
# U1 v8 a- V8 K# R  theme(axis.text.x=element_text(angle=0,colour="white",size=2,hjust=1))+
/ {0 G% }' h9 {5 L7 o( x3 k2 P   theme(panel.grid =element_blank()) +   ## 删去网格线
$ C$ q7 X* V- ]* z' G  theme(axis.text = element_blank()) +   ## 删去所有刻度标签
# E9 N2 D; C- [& Y  theme(axis.ticks = element_blank()) +  ## 删去所有刻度线
( x: T; E* Y: s* K% ]# Here comes the gganimate specific bits
#labs(title = '日期:', x = '省份', y = '累计确诊病例') +
2 Z1 T* q7 G/ s& b. B# O4 f& S#annotate("text",x=0,y=40,label=C,parse=T)+
& c( C+ k( z4 F" x4 Ccoord_flip()+
# q% O$ c" M) `6 ~transition_manual(frames=as.Date(Date)) +
3 w/ ]* Z! W- m0 e" B# h6 Q#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')
/ I( q7 [) ^( T: J1 X9 S1 Ops
- G0 h) Y7 M# A9 x3 P6 b结果展示

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视频格式转化，加载BGM
#df <- animate(ps, renderer = av_renderer('animation.mp4'),
5 p: \; c# J: W         #     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
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' c" ]. c, p# I* R" m! f2 }pc<-ggplot(data=CNdata_s,aes(x=variable,y=value,fill=variable,frame=Date))+
* ?) b9 i, m5 o3 J   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") +
  theme(panel.background=element_rect(fill='transparent'))+
9 E3 K2 f' i. g/ v5 e/ _# U  theme(axis.text.x=element_text(angle=0,colour="black",size=15,hjust=1))+
1 W& U. K; y' g" J/ x" G  theme(axis.text.y=element_text(angle=0,colour="white",size=2,hjust=1))+
' `6 A7 H. X4 \3 M   theme(panel.grid =element_blank()) +   ## 删去网格线
  theme(axis.text = element_blank()) +   ## 删去所有刻度标签
2 f$ X5 T  B' q* k; L/ x+ X8 L  theme(axis.ticks = element_blank()) +  ## 删去所有刻度线
( X! p- @! d1 d% ^! T  #scale_x_continuous(limits = c(0,6))+
8 z7 X5 R" D/ S# H% f # 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)) +
" \" m$ g# ?; B' f. w0 b5 K" x    # 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)
' m" V2 ^& b6 t: S9 m5 ?' Fps_gif <- animate(ps,,width = 720, height = 480)
pc_gif <- animate(pc, width = 360, height = 480)
) @. {5 D4 h  C: A8 H6 Wps_gifs <- image_read(ps_gif)
' Y4 N8 I  f+ Gpc_gifs <- image_read(pc_gif)
3 f3 ?# }0 v3 ]. R3 [new_gif <- image_append(c(pc_gifs[1], ps_gifs[1]))
5 G! M+ L/ }( D0 ], r) B9 cfor(i in 2:length(pc_gifs)){
  combined <- image_append(c(pc_gifs, ps_gifs))
  new_gif <- c(new_gif, combined)
}
4 ~5 y9 ~8 L8 W  f' gnew_gif
结果展示

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