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)
: D# _$ c6 h* c. M* ilibrary(ggplot2)
2 A0 C, A+ j  k) Llibrary(gganimate)
library(tidyverse)
: X5 N! F$ T# \" T6 `library(lubridate)
library(scales)
" q. H! [; X6 A# ^; n# u3 y1 Vlibrary(ggrepel)
% _$ w7 X" q0 k0 p  T0 K1 D5 e+ c7 X7 klibrary(cowplot)
- D( Z% C& w5 |% ]; [数据
: W6 {% K4 k( p2 P- D2 {

ps = ggplot(mydatan, aes(x=reorder(省份, 累计确诊),y=累计确诊, fill=省份,frame=Date)) +
- J1 ^" E7 s# e3 V1 ]     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") +
    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))+
0 H2 K; J7 N4 N/ t6 g  theme(axis.text.x=element_text(angle=0,colour="white",size=2,hjust=1))+
- F! Q$ ~: x) @& Y5 f6 Z: \   theme(panel.grid =element_blank()) +   ## 删去网格线
  theme(axis.text = element_blank()) +   ## 删去所有刻度标签
, S; R) w$ F/ U' D% K5 |  theme(axis.ticks = element_blank()) +  ## 删去所有刻度线
' X: e0 _: `: s; U9 T# 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)+
, q( A) E& a# Q9 |1 ]coord_flip()+
transition_manual(frames=as.Date(Date)) +
" E; d: i0 f* P5 v) `7 Y  T#ggdark::dark_theme_bw() + #设置黑色主题
% e7 K6 C; L1 Q) ]labs(title = paste('日期:', '{current_frame}'),x = '', y ='各省累计确诊病例增长(除湖北省外)')+
  h2 L  X' r7 a$ S  A( iease_aes('linear')
7 `2 P" ?% w* X, k' w5 kps
结果展示


9 K' L9 Q+ {" Q3 W9 G# Y视频格式转化，加载BGM
#df <- animate(ps, renderer = av_renderer('animation.mp4'),
9 ~, d; p8 Y' J  C( Y1 p         #     width = 1280, height = 720, res = 100, fps = 10)#视频制作
5 M& @+ p8 X) ]# av_encode_video(df, 'output.mp4', framerate = 2,audio ="N.mp3")
全国新冠状肺炎26天增长状况
; L+ a* w4 H# j( l* z/ @
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))+
/ J+ Q( [' V4 w3 \  theme(axis.text.y=element_text(angle=0,colour="white",size=2,hjust=1))+
   theme(panel.grid =element_blank()) +   ## 删去网格线
/ \+ B4 q! k2 F& G9 G2 `6 E  theme(axis.text = element_blank()) +   ## 删去所有刻度标签
4 b: M' @8 W9 E! p  theme(axis.ticks = element_blank()) +  ## 删去所有刻度线
  #scale_x_continuous(limits = c(0,6))+
9 Z" \: [5 W* P) ^. q. v # 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()+
! R3 {# s( ~: ~; x     transition_manual(frames=as.Date(Date)) +
6 T  K  q% ^& `    # 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

$ c: T" W0 D' F, m0 ^
动态图合并
library(magick)
+ M4 g1 [, E- |- Ups_gif <- animate(ps,,width = 720, height = 480)
0 w- ?2 V6 q" i1 q- spc_gif <- animate(pc, width = 360, height = 480)
* Y* N. g1 b+ b. U/ y+ m  `8 {1 l" R3 Aps_gifs <- image_read(ps_gif)
pc_gifs <- image_read(pc_gif)
& L/ x; ?6 x  E% v6 ?new_gif <- image_append(c(pc_gifs[1], ps_gifs[1]))
: N0 Q) n7 ?" X$ C2 F, Hfor(i in 2:length(pc_gifs)){
  combined <- image_append(c(pc_gifs, ps_gifs))
  new_gif <- c(new_gif, combined)
7 G/ x( ?) v( z( g7 C9 |}
5 O& R" R" a1 B+ c3 bnew_gif
' i5 x) B+ D' u* v- E1 z4 p结果展示


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