R语言gganimate疫情数据动态可视化

1047521767

R语言gganimate学习
. R) P  z2 E5 |  p$ d所需加载包
, P8 J9 E" |- x5 b, F$ ^8 Olibrary(av)
: w% f4 Q# |2 O9 D: X5 P2 wlibrary(ggplot2)
) z0 o/ \  w& {library(gganimate)
5 @2 U7 `: I3 `6 S, G5 S7 s# k1 Llibrary(tidyverse)
; `" n: ?; S6 b% Y& Alibrary(lubridate)
library(scales)
library(ggrepel)
6 O0 L, O$ @3 @  jlibrary(cowplot)
数据
0 e# t, {7 L; j/ C

9 u) e5 e8 a& r8 b: c; R# b0 dps = ggplot(mydatan, aes(x=reorder(省份, 累计确诊),y=累计确诊, fill=省份,frame=Date)) +
# R) c1 N8 c. M8 Y( w( N7 ?     geom_bar(stat= 'identity', position = 'dodge',show.legend = FALSE) +
4 X6 l. j2 w' y. t+ e+ t1 Z% q" ~    geom_text(aes(label=paste0(累计确诊)),col="black",hjust=-0.2)+
    #theme_bw()+
2 i9 e+ U( C1 v$ U  f2 U& j   #theme(legend.position="none") +
    theme(axis.text.x = element_text(size = 12,angle = 90, hjust = 0.2, vjust = 0.2),legend.position="none") +
$ D: l) ?3 S" }& `- h6 T' G' Y! {    theme(panel.background=element_rect(fill='transparent'))+
8 }( Q: s% c7 N  }8 b) j8 I2 z  theme(axis.text.y=element_text(angle=0,colour="black",size=12,hjust=1))+
, ~7 _0 F: I% c; |- u/ {  theme(axis.text.x=element_text(angle=0,colour="white",size=2,hjust=1))+
   theme(panel.grid =element_blank()) +   ## 删去网格线
9 _* I, G; u8 S; L' x8 p0 l- p  R  theme(axis.text = element_blank()) +   ## 删去所有刻度标签
' Y( {3 T5 S% O0 r  theme(axis.ticks = element_blank()) +  ## 删去所有刻度线
% T7 s# W& z5 k/ s# Here comes the gganimate specific bits
# l$ W# r* y5 a1 A9 a: ?#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 Y! m8 [: v1 j3 Kcoord_flip()+
transition_manual(frames=as.Date(Date)) +
#ggdark::dark_theme_bw() + #设置黑色主题
' y+ ^# g5 j7 l- c; ^! Mlabs(title = paste('日期:', '{current_frame}'),x = '', y ='各省累计确诊病例增长(除湖北省外)')+
# i7 K; y, h1 Y$ Oease_aes('linear')
ps
4 i& r* L) E9 m8 H6 b4 L" N结果展示

5 Q1 {1 w2 ~: P% P0 [3 b! V# c6 b
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
* S9 X- V! q+ `9 Z# av_encode_video(df, 'output.mp4', framerate = 2,audio ="N.mp3")
全国新冠状肺炎26天增长状况
1 d& w3 M+ ?% s$ S8 ?: h/ A
4 s7 g& Z: z$ ]  |  H; l0 s9 T! ?pc<-ggplot(data=CNdata_s,aes(x=variable,y=value,fill=variable,frame=Date))+
2 u* q/ o, [% \1 t# }- |# e   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'))+
8 r+ b7 t8 w7 \" G5 V- n  theme(axis.text.x=element_text(angle=0,colour="black",size=15,hjust=1))+
5 l+ t. h, c5 q' M9 B  theme(axis.text.y=element_text(angle=0,colour="white",size=2,hjust=1))+
6 t- L4 z6 G) T   theme(panel.grid =element_blank()) +   ## 删去网格线
  d7 q/ S5 s3 M  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
. y2 g: g; z2 g! P* l' m  #scale_x_continuous(limits = c(0,6))+
" @6 e5 e1 G' w) g# Y # Here comes the gganimate specific bits
1 l  {. p) ^. F9 C* c: j8 R#labs(title = '日期:', x = '省份', y = '累计确诊病例') +
#annotate("text",x=0,y=40,label=C,parse=T)+
: i1 G  \5 |. h2 N5 n6 _+ P    # 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 = '全国新冠状肺炎增长', y ='')+
: t& F4 C: \4 M7 X/ J- g7 E+ k; Z; h     ease_aes('linear')
pc
! V2 ]- X# n" h( Q; I

动态图合并
library(magick)
5 r7 {8 v+ R. p: V! z, Xps_gif <- animate(ps,,width = 720, height = 480)
pc_gif <- animate(pc, width = 360, height = 480)
7 A+ p7 d( q/ }ps_gifs <- image_read(ps_gif)
* X( ~1 k- {9 I9 qpc_gifs <- image_read(pc_gif)
new_gif <- image_append(c(pc_gifs[1], ps_gifs[1]))
for(i in 2:length(pc_gifs)){
- K  P7 z3 Z- |3 q$ u  combined <- image_append(c(pc_gifs, ps_gifs))
! [9 D9 z* y& M& p! I  [  new_gif <- c(new_gif, combined)
# a) x$ f1 [6 y2 n. D' \" w}
0 k; p( S& z/ L& m. znew_gif
结果展示



6 b! a7 \- ?* f( z. @  ^

sjlxdn

111111111111
3 N- H4 Y/ |6 {0 D0 b6 i