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
- h, G  z( k% O5 h9 ylibrary(av)
) Y) l  O+ S, F0 l( G( y3 V; `library(ggplot2)
library(gganimate)
+ }3 p4 N* d0 n6 `5 qlibrary(tidyverse)
library(lubridate)
. q- w, p0 @/ g6 _3 Clibrary(scales)
library(ggrepel)
library(cowplot)
数据
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ps = ggplot(mydatan, aes(x=reorder(省份, 累计确诊),y=累计确诊, fill=省份,frame=Date)) +
) P* o3 l/ \/ n" V6 d9 r     geom_bar(stat= 'identity', position = 'dodge',show.legend = FALSE) +
+ a4 `! g1 Z! H5 C1 v    geom_text(aes(label=paste0(累计确诊)),col="black",hjust=-0.2)+
. \& R7 `# N0 t2 E    #theme_bw()+
+ E  `3 N% n9 ?7 S   #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'))+
7 y7 d) S. T! F8 {2 h8 H3 c: o  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
4 m" y) A' y, S3 U4 `  theme(axis.ticks = element_blank()) +  ## 删去所有刻度线
( u( M% ]& m9 p/ I# O4 G. i# 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)) +
& j. g* @3 `- J: \; @/ h" w1 z#ggdark::dark_theme_bw() + #设置黑色主题
, `8 g( I0 y2 F% s. C( [6 H! flabs(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
: s1 S" \. d; \0 w5 o# F9 O/ ^结果展示
* s7 v  \+ R( p/ g: z* E  E! T

5 ~# B' G" r1 {; f$ E4 }. L视频格式转化，加载BGM
3 Z1 `7 b+ }% w2 l( D#df <- animate(ps, renderer = av_renderer('animation.mp4'),
         #     width = 1280, height = 720, res = 100, fps = 10)#视频制作
2 s; A% N. N& |& h% ]1 |# av_encode_video(df, 'output.mp4', framerate = 2,audio ="N.mp3")
4 N$ w9 T& s) ]1 A9 F全国新冠状肺炎26天增长状况
9 i7 s% d( {3 W9 g. H& l
- ?: N5 s/ d7 x; [) k* u2 s* J; _* fpc<-ggplot(data=CNdata_s,aes(x=variable,y=value,fill=variable,frame=Date))+
. ?! |( i6 m& K8 c2 X+ B   geom_bar(stat= 'identity', position = 'dodge',show.legend = FALSE,width=0.7) +
   geom_text(aes(label=paste0(value)),col="black",hjust=-0.2)+
* q/ `5 |9 l/ ^" f0 l- f4 v    theme(legend.position="none") +
  theme(panel.background=element_rect(fill='transparent'))+
0 ]1 ?4 F7 \9 ^  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
  theme(axis.ticks = element_blank()) +  ## 删去所有刻度线
. r4 U" A  r" E  #scale_x_continuous(limits = c(0,6))+
; i- E" i" a4 C* p5 i  W- B # Here comes the gganimate specific bits
7 x8 {8 f1 P0 d0 l#labs(title = '日期:', x = '省份', y = '累计确诊病例') +
5 Q7 j+ J; B! p- V0 d) K#annotate("text",x=0,y=40,label=C,parse=T)+
    # coord_flip()+
     transition_manual(frames=as.Date(Date)) +
8 k4 H0 X7 h  u* J    # 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 ='')+
4 @$ r0 ], q  y6 O/ f     ease_aes('linear')
pc

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) j$ q7 i) {% Q% O6 A动态图合并
library(magick)
9 J( |( v* u1 [ps_gif <- animate(ps,,width = 720, height = 480)
pc_gif <- animate(pc, width = 360, height = 480)
ps_gifs <- image_read(ps_gif)
9 g3 a4 F* ]6 t. X5 r+ |) q2 _' Opc_gifs <- image_read(pc_gif)
new_gif <- image_append(c(pc_gifs[1], ps_gifs[1]))
$ l) l& T7 I$ a/ j- dfor(i in 2:length(pc_gifs)){
  combined <- image_append(c(pc_gifs, ps_gifs))
! L7 l) |) j' x  new_gif <- c(new_gif, combined)
$ A5 T! R% I* T% {/ _}
new_gif
9 j) [. C# h0 {  e1 Z, E结果展示


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