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标题: R语言gganimate疫情数据动态可视化 [打印本页]

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作者: 1047521767    时间: 2021-10-28 19:38
标题: R语言gganimate疫情数据动态可视化
R语言gganimate学习
所需加载包
7 H4 R4 B7 B+ z$ S1 F# v( q0 }1 Qlibrary(av)
library(ggplot2)
  U% n% E  y) i: klibrary(gganimate)
library(tidyverse)
library(lubridate)
. x1 K6 I2 `4 D* ~. [& s! Y# ]library(scales)
0 S# I' f1 E% l. I4 k1 z& |library(ggrepel)
library(cowplot)
. \3 }% \) H" t数据
( `  V" B* ~) i9 w' J, x& t

- c' n5 \! b; M- u' j8 i# vps = ggplot(mydatan, aes(x=reorder(省份, 累计确诊),y=累计确诊, fill=省份,frame=Date)) +
, I  S% {/ v$ S7 j     geom_bar(stat= 'identity', position = 'dodge',show.legend = FALSE) +
; V6 a% \% t" ]9 o% b* N! r+ d    geom_text(aes(label=paste0(累计确诊)),col="black",hjust=-0.2)+
" o! ?7 `( c8 B. P  o4 S' u    #theme_bw()+
   #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))+
  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
3 {) K. w. J2 v- M  theme(axis.ticks = element_blank()) +  ## 删去所有刻度线
# Here comes the gganimate specific bits
  m) n; X( N9 |7 k- X#labs(title = '日期:', x = '省份', y = '累计确诊病例') +
#annotate("text",x=0,y=40,label=C,parse=T)+
) G5 ?8 @8 \# V4 F: i- j* Kcoord_flip()+
transition_manual(frames=as.Date(Date)) +
#ggdark::dark_theme_bw() + #设置黑色主题
" K+ b# V$ c6 k$ j. A8 K& g$ Vlabs(title = paste('日期:', '{current_frame}'),x = '', y ='各省累计确诊病例增长(除湖北省外)')+
0 {- S; x& i! q9 fease_aes('linear')
8 N8 L8 I, I6 d* s9 \- J  cps
: [  @! S& k1 p结果展示
6 V+ J9 w6 T' R6 c8 Z( ?1 ^& W$ \9 f
. D* M) r. z# {% G9 l& T- O- Q( f# u2 M
1 E3 A! d( Z& Z8 l  _; P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
' w3 s! f4 |* c3 |+ Y4 @' Y' \9 T# av_encode_video(df, 'output.mp4', framerate = 2,audio ="N.mp3")
) N6 [! U- w. F( g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))+
   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") +
9 j7 Q+ i! Z5 c7 U9 u5 [4 g  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))+
/ Y  L' h2 w  a   theme(panel.grid =element_blank()) +   ## 删去网格线
9 K0 p) x+ E( ~3 m8 N. B7 Z% }% v8 f3 i  theme(axis.text = element_blank()) +   ## 删去所有刻度标签
- C8 o/ m% f8 O8 b  theme(axis.ticks = element_blank()) +  ## 删去所有刻度线
; A! O* g  o+ K* a  #scale_x_continuous(limits = c(0,6))+
# Here comes the gganimate specific bits
" ?2 u6 t3 F* n+ U/ 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)+
    # 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 ='')+
     ease_aes('linear')
' f7 \8 }- E) ?3 Xpc
6 j) X' O; b! q  R% r: i1 T
- z2 u9 E* p" \0 F& ^! A
动态图合并
1 G6 A* M+ w/ k1 R% jlibrary(magick)
- D6 q% D/ `0 i3 C" eps_gif <- animate(ps,,width = 720, height = 480)
  \: O/ \: m8 n& n/ Tpc_gif <- animate(pc, width = 360, height = 480)
ps_gifs <- image_read(ps_gif)
/ X, a* v9 W  g# `pc_gifs <- image_read(pc_gif)
" y: c. E9 y  f! _+ d: d, |new_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)
}
new_gif
# W7 z2 D1 S. {; A* ]6 `! r4 ~3 j结果展示


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作者: sjlxdn    时间: 2021-10-29 12:57
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