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
1 q" @: W; t3 f3 i, o0 Ulibrary(av)
+ E( b4 b% Z% g4 t3 m$ ^, wlibrary(ggplot2)
$ C4 T7 m# x" [, Klibrary(gganimate)
library(tidyverse)
/ |$ c$ }& h- V" ]7 `library(lubridate)
: L+ \, d$ a8 V: C- h5 {  p8 glibrary(scales)
library(ggrepel)
! f3 o  d- G+ m/ s7 J, s" B! {7 c! K; ulibrary(cowplot)
数据


% U9 N/ s0 x8 _, b$ Zps = ggplot(mydatan, aes(x=reorder(省份, 累计确诊),y=累计确诊, fill=省份,frame=Date)) +
4 Z. S* M: \. }5 ?% Q4 l- l     geom_bar(stat= 'identity', position = 'dodge',show.legend = FALSE) +
9 O. r& K4 ~4 g  ?! W    geom_text(aes(label=paste0(累计确诊)),col="black",hjust=-0.2)+
1 r4 s' Q$ E; `) H  F    #theme_bw()+
( q# N  t, |* o; [9 s$ s! g   #theme(legend.position="none") +
2 q8 N3 d8 S0 T! \; e+ y  n4 U4 d    theme(axis.text.x = element_text(size = 12,angle = 90, hjust = 0.2, vjust = 0.2),legend.position="none") +
/ }, x8 s' p6 r* }( q9 R6 {    theme(panel.background=element_rect(fill='transparent'))+
  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
3 ~) U* D- ^& Q8 o! n  S3 L# r  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
* o! ]& t3 X7 p" D# Here comes the gganimate specific bits
# @& V* C7 f  M2 |& n/ w#labs(title = '日期:', x = '省份', y = '累计确诊病例') +
#annotate("text",x=0,y=40,label=C,parse=T)+
0 p/ d$ ?7 u$ h! E; ^coord_flip()+
transition_manual(frames=as.Date(Date)) +
#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
结果展示

* H( a1 a% l/ A: d- B3 |; m% y
视频格式转化，加载BGM
#df <- animate(ps, renderer = av_renderer('animation.mp4'),
# _- u5 M( X- Q/ K4 ^8 v         #     width = 1280, height = 720, res = 100, fps = 10)#视频制作
! t. t& g9 o" l5 R( Z# av_encode_video(df, 'output.mp4', framerate = 2,audio ="N.mp3")
& Z! `8 a% i5 \  H" K; E全国新冠状肺炎26天增长状况
4 d+ G5 d# l& o! ~- ~! d0 W
' c& }. a4 D, ^$ h, t0 X0 Fpc<-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) +
5 w& N5 \; @8 [" y2 |- t1 D   geom_text(aes(label=paste0(value)),col="black",hjust=-0.2)+
+ c2 b2 r% c0 c/ ^% ^8 R    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))+
% h! N) D5 R9 o& W: W  theme(axis.text.y=element_text(angle=0,colour="white",size=2,hjust=1))+
7 z8 q# y4 E0 a: {5 _   theme(panel.grid =element_blank()) +   ## 删去网格线
0 f& M* A9 m" T. P$ M) _3 D5 G  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') +
5 M3 B. W; U! a4 U$ X& \#annotate("text",x=0,y=40,label=C,parse=T)+
    # coord_flip()+
/ t) ^" f* r& n4 [9 l0 z     transition_manual(frames=as.Date(Date)) +
    # ggdark::dark_theme_bw() + #设置黑色主题
, B1 M0 ^: Y: y0 z) b     labs(title = paste('日期:', '{current_frame}'),x = '全国新冠状肺炎增长', y ='')+
2 x# y7 w; c9 J/ A$ j; v9 ~     ease_aes('linear')
pc
( A* N, N3 s, }# y2 r. w
0 e2 V9 L5 |. ~7 @' Q% o
动态图合并
library(magick)
) G6 M6 U  t2 `  L/ C, Z. s- A! }ps_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)
new_gif <- image_append(c(pc_gifs[1], ps_gifs[1]))
! |1 G' m$ Z) H) a0 ufor(i in 2:length(pc_gifs)){
" G7 U6 a+ h! q+ k3 E  combined <- image_append(c(pc_gifs, ps_gifs))
* D- w2 |  M0 {+ R  new_gif <- c(new_gif, combined)
}
9 g; X) }. @! B; ~, ~) Fnew_gif
结果展示
9 z7 D7 S( K% ?( S) e1 R

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