R语言gganimate疫情数据动态可视化

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R语言gganimate学习
" R+ H, s% Z: x3 J  ^所需加载包
library(av)
0 ?8 w5 U& q+ C0 T, I, Ylibrary(ggplot2)
! Q, Y5 J* r. u5 {0 O2 C% m) Y7 Tlibrary(gganimate)
library(tidyverse)
5 a/ p4 {9 C9 q( H! n/ ]% F( slibrary(lubridate)
library(scales)
4 r8 f+ N6 j8 m) |, X& [* ylibrary(ggrepel)
library(cowplot)
数据


1 m8 |1 A9 I0 C+ V0 H9 O2 Kps = 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) +
& E4 }5 }* ]# f% X: C; s* N    geom_text(aes(label=paste0(累计确诊)),col="black",hjust=-0.2)+
: V, g, }* m3 s# c4 R4 |    #theme_bw()+
2 N% ?  n+ y: X# s: o   #theme(legend.position="none") +
2 C! x9 `5 d. N  W8 {/ _    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'))+
- k; k# \! I; [* G$ o' r# l  theme(axis.text.y=element_text(angle=0,colour="black",size=12,hjust=1))+
0 m6 }0 M) R2 U; u3 h  G0 H' i  theme(axis.text.x=element_text(angle=0,colour="white",size=2,hjust=1))+
" m7 t: Z+ A, ~  G% ?% x" ]   theme(panel.grid =element_blank()) +   ## 删去网格线
0 R+ W$ }' F. V. ^  theme(axis.text = element_blank()) +   ## 删去所有刻度标签
! D' G) r$ m. O1 t  theme(axis.ticks = element_blank()) +  ## 删去所有刻度线
, c' Y# L) J" [6 \# Here comes the gganimate specific bits
$ N0 K! C3 f! r( r#labs(title = '日期:', x = '省份', y = '累计确诊病例') +
* |7 d- D# Z; L1 u1 B#annotate("text",x=0,y=40,label=C,parse=T)+
coord_flip()+
0 x* Z7 i; [, @0 H2 j. J, Ctransition_manual(frames=as.Date(Date)) +
7 w# O% B! U6 V; `: J#ggdark::dark_theme_bw() + #设置黑色主题
7 d' Z( h* }" H$ zlabs(title = paste('日期:', '{current_frame}'),x = '', y ='各省累计确诊病例增长(除湖北省外)')+
6 ]% @# Y7 F% eease_aes('linear')
( z9 X4 O' ^5 c  S3 H: O9 s  gps
0 ^7 D+ Q& f0 X1 |% |( g结果展示
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视频格式转化，加载BGM
9 n4 q# h: x- b- H- d8 i& H" t#df <- animate(ps, renderer = av_renderer('animation.mp4'),
6 a# w' R/ z, C3 w- @! ]( W         #     width = 1280, height = 720, res = 100, fps = 10)#视频制作
8 }/ M6 v' ?. m& M) J: o, _7 q# av_encode_video(df, 'output.mp4', framerate = 2,audio ="N.mp3")
, H& m1 z$ _. w' w全国新冠状肺炎26天增长状况
1 _& |% l1 S( b8 e
' L9 R; Z; ?5 Cpc<-ggplot(data=CNdata_s,aes(x=variable,y=value,fill=variable,frame=Date))+
8 \! \6 \- O8 U$ d3 {# Q   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") +
/ ~& {/ o, n5 m0 ~" d6 O" K  theme(panel.background=element_rect(fill='transparent'))+
. v2 Y( H; m3 P  n  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))+
1 @; ]5 i2 F' B/ O! h2 K1 b   theme(panel.grid =element_blank()) +   ## 删去网格线
3 p3 T9 I1 v) h0 Y  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))+
5 ?% Q! Y8 s) b) U# W) B* s- c # Here comes the gganimate specific bits
# r& w3 a% y, e) ^, O#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)) +
* d. p4 w( y1 B    # ggdark::dark_theme_bw() + #设置黑色主题
, m" k9 j$ d: w' _     labs(title = paste('日期:', '{current_frame}'),x = '全国新冠状肺炎增长', y ='')+
. I  Z5 Q2 H8 r5 Y+ z     ease_aes('linear')
pc


动态图合并
, V6 Z+ y: Z& m8 dlibrary(magick)
7 W% g! L5 {* W: zps_gif <- animate(ps,,width = 720, height = 480)
9 f) m1 p+ K# x1 H7 b7 Npc_gif <- animate(pc, width = 360, height = 480)
8 N6 G- H- c. Ups_gifs <- image_read(ps_gif)
/ c' ]: \3 o7 k& Npc_gifs <- image_read(pc_gif)
( E; }/ Q. i* [/ {' h7 [2 S8 cnew_gif <- image_append(c(pc_gifs[1], ps_gifs[1]))
for(i in 2:length(pc_gifs)){
5 M: h# ~8 [$ N7 c& M* E  combined <- image_append(c(pc_gifs, ps_gifs))
# j' b! |2 [* y8 v  new_gif <- c(new_gif, combined)
: K$ K0 R1 _; O4 `( G}
# P2 a% w4 x+ rnew_gif
1 O/ N" ?4 \# i1 I结果展示
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