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
4 C4 g2 m' |* k2 F; m$ Olibrary(av)
library(ggplot2)
library(gganimate)
6 }# m) v+ k9 _( P; \7 Glibrary(tidyverse)
/ A/ J: f* ~5 v6 P! K3 Clibrary(lubridate)
library(scales)
8 v. M, E8 c7 Y+ R4 P7 |library(ggrepel)
/ M' V/ {4 e4 m: Z+ c  J7 b' e$ [) dlibrary(cowplot)
* c! F8 N5 i/ _数据
+ Y# }' w9 I4 Y$ ]4 v

ps = ggplot(mydatan, aes(x=reorder(省份, 累计确诊),y=累计确诊, fill=省份,frame=Date)) +
6 Z1 L8 v& }$ b     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") +
# @5 t- k3 X; w/ f    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'))+
  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
# O$ O* c+ B/ b& p" L  theme(axis.ticks = element_blank()) +  ## 删去所有刻度线
" T0 c3 q7 r- d0 Q9 ^# 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)+
# @3 k  T6 O3 Z- kcoord_flip()+
+ ]6 V$ g% z* dtransition_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
: A+ f' ?0 x% n2 O+ ?' A: M结果展示
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- ~  m. j8 W( f- Q视频格式转化，加载BGM
/ L/ [% Z' w' x, x  {- b! Y; q#df <- animate(ps, renderer = av_renderer('animation.mp4'),
" Y2 ]0 j$ t( O  p3 I" c         #     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
# G" `/ g8 R$ Z. V
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) +
   geom_text(aes(label=paste0(value)),col="black",hjust=-0.2)+
    theme(legend.position="none") +
  theme(panel.background=element_rect(fill='transparent'))+
  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))+
& w( L& j. ^9 i3 K   theme(panel.grid =element_blank()) +   ## 删去网格线
! K: o5 c$ Y) y7 N  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
* h" q9 \8 ^9 u1 l7 t, ?#labs(title = '日期:', x = '省份', y = '累计确诊病例') +
. ^' j' Z: n" D; L: l1 A7 C" J) K#annotate("text",x=0,y=40,label=C,parse=T)+
0 O" c* X  M! P/ b- R) j" z! f    # coord_flip()+
& W* d4 Z5 i" _     transition_manual(frames=as.Date(Date)) +
. H1 F7 i- ^8 g8 V    # 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 ='')+
' `8 n: v9 d# U5 Z     ease_aes('linear')
9 N5 F  p( E7 z" v; Rpc
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动态图合并
: F$ U& ~* ^+ l9 \/ t5 Llibrary(magick)
ps_gif <- animate(ps,,width = 720, height = 480)
4 X2 w5 O" x" L  w3 S' b7 i* Opc_gif <- animate(pc, width = 360, height = 480)
ps_gifs <- image_read(ps_gif)
$ @) n( p3 {" E$ y# ~6 epc_gifs <- image_read(pc_gif)
new_gif <- image_append(c(pc_gifs[1], ps_gifs[1]))
; n, D; t$ q. V7 D# a/ O6 Ofor(i in 2:length(pc_gifs)){
  combined <- image_append(c(pc_gifs, ps_gifs))
$ X+ M: g  W" c- C* S' U9 }  new_gif <- c(new_gif, combined)
}
new_gif
1 N5 w  ]' j: G结果展示

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