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)
% }" ~+ Z' y* q# w$ flibrary(ggplot2)
library(gganimate)
8 P3 A. l6 b5 l; H5 e9 Blibrary(tidyverse)
; ]4 F" f/ D' I- x! J$ ~library(lubridate)
+ H0 c: r, {- \; X. Plibrary(scales)
5 _& v; v! q7 t6 p4 u! d; k$ E, \! Dlibrary(ggrepel)
library(cowplot)
数据

; _( L. O# T+ `
5 O! @9 {6 ^, r% `& l2 t, rps = ggplot(mydatan, aes(x=reorder(省份, 累计确诊),y=累计确诊, fill=省份,frame=Date)) +
& h4 g( W" U: O9 w3 {# L     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") +
5 Q" D1 d" I* ]7 H7 w0 u    theme(axis.text.x = element_text(size = 12,angle = 90, hjust = 0.2, vjust = 0.2),legend.position="none") +
& `0 _8 P* H# `7 D    theme(panel.background=element_rect(fill='transparent'))+
( M( d: q" Y3 H3 t. S' ]/ {9 ?3 i  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 c& Q" {1 T- f) N8 B; [8 \" F# x9 l$ x  theme(axis.ticks = element_blank()) +  ## 删去所有刻度线
# Here comes the gganimate specific bits
- F4 N, l6 g! x( u+ O) ^9 {/ T' I9 @#labs(title = '日期:', x = '省份', y = '累计确诊病例') +
) K& Z5 r, @/ X#annotate("text",x=0,y=40,label=C,parse=T)+
# [, f, ^+ {9 h0 H' scoord_flip()+
  D. G! t7 Y: H# N; Ltransition_manual(frames=as.Date(Date)) +
( }2 k, `9 [+ T$ @% J5 Z5 g0 Q#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
1 w. O: \4 T+ A% d" U3 ]! D6 J结果展示
- \. w+ S1 D! M. W# l4 a

视频格式转化，加载BGM
#df <- animate(ps, renderer = av_renderer('animation.mp4'),
         #     width = 1280, height = 720, res = 100, fps = 10)#视频制作
8 W8 U  _# w  R6 s/ Q# av_encode_video(df, 'output.mp4', framerate = 2,audio ="N.mp3")
& I( t3 I8 k# }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))+
   geom_bar(stat= 'identity', position = 'dodge',show.legend = FALSE,width=0.7) +
# Q$ P% n" p- I& M0 z! D   geom_text(aes(label=paste0(value)),col="black",hjust=-0.2)+
    theme(legend.position="none") +
  `1 u  S! p6 V: ~- P; F* ?: t  theme(panel.background=element_rect(fill='transparent'))+
  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))+
7 m) d5 q, U9 I0 f% V& z0 u   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
  #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()+
     transition_manual(frames=as.Date(Date)) +
    # ggdark::dark_theme_bw() + #设置黑色主题
8 Z) r! |, f8 j5 s8 h8 I$ m     labs(title = paste('日期:', '{current_frame}'),x = '全国新冠状肺炎增长', y ='')+
* m+ L3 Z2 ]9 T* w. z, [, C     ease_aes('linear')
- l6 r7 o2 I8 G' |' |4 \) W/ ppc

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动态图合并
library(magick)
ps_gif <- animate(ps,,width = 720, height = 480)
9 n+ Q4 i5 I" }! R; C5 jpc_gif <- animate(pc, width = 360, height = 480)
ps_gifs <- image_read(ps_gif)
2 m" K" O, t/ ^, a" |pc_gifs <- image_read(pc_gif)
, H& \  X. y  F8 Pnew_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)
7 C) A, @) g) \6 W. _}
% n4 U( F% Q6 _# pnew_gif
结果展示

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