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)
library(gganimate)
library(tidyverse)
library(lubridate)
library(scales)
library(ggrepel)
library(cowplot)
* T4 v1 j9 v7 o  e/ ^) y: u- z数据
' z8 r3 e9 p" z9 z: ]# ?

* |. M: V+ k4 G% H9 jps = 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) +
# E* _' n6 g; t/ y0 ]    geom_text(aes(label=paste0(累计确诊)),col="black",hjust=-0.2)+
6 e) G3 c4 K4 u! ^  q2 [+ c" X    #theme_bw()+
4 b+ A) B" k5 K& \8 a   #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'))+
  theme(axis.text.y=element_text(angle=0,colour="black",size=12,hjust=1))+
& b7 T, Y# L, V+ T- I% b  theme(axis.text.x=element_text(angle=0,colour="white",size=2,hjust=1))+
   theme(panel.grid =element_blank()) +   ## 删去网格线
/ a6 M+ ?. q( K4 r  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
- E4 }( u( K5 e# 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()+
6 p0 @, i3 \0 }6 C2 d5 a% Htransition_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
7 {. I) v  a8 ~( ?$ B结果展示
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# R, O! }' r6 ?1 f5 |3 e
9 U$ F  h$ K" d# H, d5 I视频格式转化，加载BGM
4 K- c: S  G2 W+ J#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")
: M+ C/ X  d( ?/ H9 S3 |( {全国新冠状肺炎26天增长状况
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pc<-ggplot(data=CNdata_s,aes(x=variable,y=value,fill=variable,frame=Date))+
: T* {& u% G, q: Q/ E   geom_bar(stat= 'identity', position = 'dodge',show.legend = FALSE,width=0.7) +
   geom_text(aes(label=paste0(value)),col="black",hjust=-0.2)+
: s3 Z; b5 x8 v8 P2 h, c' w    theme(legend.position="none") +
# J: W" W; _! u0 ~  theme(panel.background=element_rect(fill='transparent'))+
  theme(axis.text.x=element_text(angle=0,colour="black",size=15,hjust=1))+
  c  U6 V3 C1 \6 W! D, {0 b7 l  theme(axis.text.y=element_text(angle=0,colour="white",size=2,hjust=1))+
+ D: `* v: P; A  P, N. G   theme(panel.grid =element_blank()) +   ## 删去网格线
$ Y" e" j) ^) N: z  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
3 R8 X' Y+ V1 U  #scale_x_continuous(limits = c(0,6))+
- [- `1 `2 U4 T+ d# W8 B  J) a  k # 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)) +
& C/ j4 L2 s0 T3 _+ T% M% \' {    # 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


0 L# E3 v1 @4 O* {. M动态图合并
library(magick)
ps_gif <- animate(ps,,width = 720, height = 480)
- F* e0 i- K8 Y0 S, x; g) Bpc_gif <- animate(pc, width = 360, height = 480)
8 w7 q! B3 m/ S7 E0 \0 rps_gifs <- image_read(ps_gif)
# _- d6 A; Z( Zpc_gifs <- image_read(pc_gif)
new_gif <- image_append(c(pc_gifs[1], ps_gifs[1]))
2 Z8 B- a7 T, o& O% i, Bfor(i in 2:length(pc_gifs)){
5 I; r" z# i. V$ {  y# N  combined <- image_append(c(pc_gifs, ps_gifs))
  new_gif <- c(new_gif, combined)
}
new_gif
. ?3 ^; ?8 D6 r- r9 M结果展示


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