R语言gganimate疫情数据动态可视化

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R语言gganimate学习
* c  V* i2 z* |1 _所需加载包
! R2 {# s: x4 X" O1 F# c( Dlibrary(av)
4 ^' o) y1 P6 \# J! |+ \; X) ilibrary(ggplot2)
library(gganimate)
library(tidyverse)
library(lubridate)
library(scales)
library(ggrepel)
library(cowplot)
2 \# V" Y) ]+ _0 [数据


ps = ggplot(mydatan, aes(x=reorder(省份, 累计确诊),y=累计确诊, fill=省份,frame=Date)) +
# J6 Z0 ^# v3 @, T. d8 j5 N% W: `     geom_bar(stat= 'identity', position = 'dodge',show.legend = FALSE) +
# x0 Y* S. q, I8 \, Z0 l8 t    geom_text(aes(label=paste0(累计确诊)),col="black",hjust=-0.2)+
; o. n" q6 g% k1 t' K) _    #theme_bw()+
, l% H/ w+ d7 \   #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))+
( A* [' h4 ^/ @, e0 D) h) Q  theme(axis.text.x=element_text(angle=0,colour="white",size=2,hjust=1))+
- T: R5 L' P- E6 n- a# [   theme(panel.grid =element_blank()) +   ## 删去网格线
  theme(axis.text = element_blank()) +   ## 删去所有刻度标签
+ c+ z  ?8 M6 y' h7 ?  theme(axis.ticks = element_blank()) +  ## 删去所有刻度线
# Here comes the gganimate specific bits
* F- }$ x- p9 a$ [9 R+ m* J#labs(title = '日期:', x = '省份', y = '累计确诊病例') +
#annotate("text",x=0,y=40,label=C,parse=T)+
1 N& Q# z- ?  ycoord_flip()+
9 a0 d( n/ d& B- v) X8 Rtransition_manual(frames=as.Date(Date)) +
7 h6 F9 j+ ]8 p: a$ ~! u  t#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)')+
5 U# H) o7 X" Z$ r* y4 mease_aes('linear')
: o7 ~0 ^# M  D" m2 H* Lps
) ^0 h4 ?# J2 S7 m" f& M* s结果展示
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视频格式转化，加载BGM
#df <- animate(ps, renderer = av_renderer('animation.mp4'),
0 q8 O2 t( K* u' j, b. Q0 i         #     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

pc<-ggplot(data=CNdata_s,aes(x=variable,y=value,fill=variable,frame=Date))+
% c) q. s4 |* z4 w  E. j   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'))+
5 R( t% G$ a: E* y7 z0 u5 x/ R: ]  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
0 X. r. f' |8 ]8 q/ S  #scale_x_continuous(limits = c(0,6))+
# 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()+
. z2 F: A* }" x/ F. i     transition_manual(frames=as.Date(Date)) +
    # 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 ='')+
5 L7 H) e% w/ X# r2 q* D) l     ease_aes('linear')
pc
& w/ x" f1 O% Q$ p6 @

动态图合并
library(magick)
; o+ U! I2 e. t' O; u( v- c( eps_gif <- animate(ps,,width = 720, height = 480)
pc_gif <- animate(pc, width = 360, height = 480)
ps_gifs <- image_read(ps_gif)
pc_gifs <- image_read(pc_gif)
1 H  p7 u3 i0 v* N- ?# nnew_gif <- image_append(c(pc_gifs[1], ps_gifs[1]))
for(i in 2:length(pc_gifs)){
  combined <- image_append(c(pc_gifs, ps_gifs))
  new_gif <- c(new_gif, combined)
8 g( A* L  t7 r# R/ z}
1 k  K6 k0 {" W; Y2 q' h: i5 vnew_gif
结果展示

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