R语言gganimate疫情数据动态可视化

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R语言gganimate学习
5 Q) c! W* q$ r所需加载包
library(av)
library(ggplot2)
, R5 z4 i* s) k- J# ^' D5 qlibrary(gganimate)
, t. l3 y# \5 R; l$ s  n- x0 l# ]library(tidyverse)
library(lubridate)
library(scales)
library(ggrepel)
library(cowplot)
数据

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6 N5 G+ \* f. @+ G: Jps = ggplot(mydatan, aes(x=reorder(省份, 累计确诊),y=累计确诊, fill=省份,frame=Date)) +
$ z2 C6 ^( f1 V  B# U% c; N# v     geom_bar(stat= 'identity', position = 'dodge',show.legend = FALSE) +
0 z1 t- A- t7 D( H! _' w( s    geom_text(aes(label=paste0(累计确诊)),col="black",hjust=-0.2)+
- f1 s5 k$ [4 e* Y3 y7 K    #theme_bw()+
   #theme(legend.position="none") +
9 B( h2 K( P+ J- n    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))+
2 U. X1 C9 r. v* [) v$ K  B  theme(axis.text.x=element_text(angle=0,colour="white",size=2,hjust=1))+
8 ], k; v# A" S" S   theme(panel.grid =element_blank()) +   ## 删去网格线
& N/ ?+ H) ?0 V+ v- ~# ?* G" m  theme(axis.text = element_blank()) +   ## 删去所有刻度标签
$ k" H3 _! o  ~0 v  theme(axis.ticks = element_blank()) +  ## 删去所有刻度线
# Here comes the gganimate specific bits
- ~! Y* X; \1 o#labs(title = '日期:', x = '省份', y = '累计确诊病例') +
; A' c) x5 N; m2 v& ^: p1 ?2 n#annotate("text",x=0,y=40,label=C,parse=T)+
5 p6 B9 b  K6 U, \! N* rcoord_flip()+
transition_manual(frames=as.Date(Date)) +
+ T0 y  C* n$ q8 }4 W#ggdark::dark_theme_bw() + #设置黑色主题
2 c# Z6 T, ]% ~8 M6 R0 Wlabs(title = paste('日期:', '{current_frame}'),x = '', y ='各省累计确诊病例增长(除湖北省外)')+
3 V: k5 y7 X% O' Y' f6 L: e( ?0 xease_aes('linear')
ps
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'),
+ ]2 z# t8 ^9 X3 _% H         #     width = 1280, height = 720, res = 100, fps = 10)#视频制作
# av_encode_video(df, 'output.mp4', framerate = 2,audio ="N.mp3")
6 ~9 d' y+ }3 l: L- v+ N' O# R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) +
   geom_text(aes(label=paste0(value)),col="black",hjust=-0.2)+
. u: ^& S( m1 f* W    theme(legend.position="none") +
7 t& _. p6 n! n# Q6 R; G( Z  theme(panel.background=element_rect(fill='transparent'))+
  theme(axis.text.x=element_text(angle=0,colour="black",size=15,hjust=1))+
) F8 M: }7 w+ m  theme(axis.text.y=element_text(angle=0,colour="white",size=2,hjust=1))+
   theme(panel.grid =element_blank()) +   ## 删去网格线
* I$ o! w1 m1 F' H" ]  theme(axis.text = element_blank()) +   ## 删去所有刻度标签
, e- N# K3 c1 K; J; ]$ |  theme(axis.ticks = element_blank()) +  ## 删去所有刻度线
  #scale_x_continuous(limits = c(0,6))+
' P+ n8 ]) a6 l  _ # Here comes the gganimate specific bits
7 T8 H- _5 T9 s6 x2 m#labs(title = '日期:', x = '省份', y = '累计确诊病例') +
, I  J( p2 _2 h( l3 Z#annotate("text",x=0,y=40,label=C,parse=T)+
8 x3 o3 \- k* @8 z' U# \( q9 q    # coord_flip()+
* C! v* ~& G# X% J+ a     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 ='')+
     ease_aes('linear')
pc

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动态图合并
library(magick)
ps_gif <- animate(ps,,width = 720, height = 480)
' P  f# c# y6 L. r8 k. r$ fpc_gif <- animate(pc, width = 360, height = 480)
ps_gifs <- image_read(ps_gif)
8 L) \: _  a, d4 T+ V9 R+ q' Xpc_gifs <- image_read(pc_gif)
6 Y: E' [. d4 }5 a: C/ L/ Dnew_gif <- image_append(c(pc_gifs[1], ps_gifs[1]))
. A+ P! w. Z6 p& q6 ifor(i in 2:length(pc_gifs)){
, B, k- R& w" k6 h  combined <- image_append(c(pc_gifs, ps_gifs))
; K, x2 Q2 V9 d& I6 Q% w) c. G. H4 E  new_gif <- c(new_gif, combined)
}
+ Y" u3 y# K7 {2 U' B  wnew_gif
% ^' K- p) L% s# |结果展示

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