R语言gganimate疫情数据动态可视化

1047521767

R语言gganimate学习
所需加载包
# B4 ^* G# V$ W5 U: K% Xlibrary(av)
library(ggplot2)
' a8 ~4 L7 V+ H2 I6 ~library(gganimate)
library(tidyverse)
library(lubridate)
. a1 l: h7 N4 v1 I" G4 m' E- j9 ^library(scales)
library(ggrepel)
library(cowplot)
& \3 o- e# Y  Z* P6 M( f3 H: P4 N数据


# ?  i( C5 s, Z$ _9 d* ~: sps = ggplot(mydatan, aes(x=reorder(省份, 累计确诊),y=累计确诊, fill=省份,frame=Date)) +
     geom_bar(stat= 'identity', position = 'dodge',show.legend = FALSE) +
' n. w' v" m+ a  y7 B5 |    geom_text(aes(label=paste0(累计确诊)),col="black",hjust=-0.2)+
    #theme_bw()+
- G* t. j) J+ M  z   #theme(legend.position="none") +
/ W; U3 {0 v! |) \2 R# v' ~7 C    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
, O6 B# t9 M1 B! Q& z  theme(axis.ticks = element_blank()) +  ## 删去所有刻度线
+ a% v1 q1 K5 P7 {* o& A( q# Here comes the gganimate specific bits
4 D3 Y: X8 r. J. s#labs(title = '日期:', x = '省份', y = '累计确诊病例') +
# U* l: Z1 R2 e#annotate("text",x=0,y=40,label=C,parse=T)+
  q1 ^  V: d* u2 p4 C: o2 r  Zcoord_flip()+
transition_manual(frames=as.Date(Date)) +
+ T! r+ d, c8 e$ q#ggdark::dark_theme_bw() + #设置黑色主题
3 m+ T- J. t, l% @# qlabs(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')
: v$ W. E8 p' K, D3 aps
结果展示
! O+ S* q: E, B2 v+ t

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
) W  t) r5 @4 K* o  I7 o# av_encode_video(df, 'output.mp4', framerate = 2,audio ="N.mp3")
+ p2 u3 Z  W: `- I% k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))+
! G* x4 @0 f# C5 U8 Z   geom_bar(stat= 'identity', position = 'dodge',show.legend = FALSE,width=0.7) +
- e% N7 s9 C& B$ B/ z   geom_text(aes(label=paste0(value)),col="black",hjust=-0.2)+
    theme(legend.position="none") +
  theme(panel.background=element_rect(fill='transparent'))+
6 b$ y3 d% `" ^# P* C  theme(axis.text.x=element_text(angle=0,colour="black",size=15,hjust=1))+
7 J+ n! d$ q1 n9 s4 D" e$ O4 f4 A  theme(axis.text.y=element_text(angle=0,colour="white",size=2,hjust=1))+
( @+ Z1 N6 j( _+ |4 U   theme(panel.grid =element_blank()) +   ## 删去网格线
  theme(axis.text = element_blank()) +   ## 删去所有刻度标签
+ S# b- C# U/ l" R4 i! j/ K) c  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
7 {; V/ D: O4 W9 V% S     labs(title = paste('日期:', '{current_frame}'),x = '全国新冠状肺炎增长', y ='')+
     ease_aes('linear')
pc


动态图合并
, J* |- \& `# K# ^1 j& [library(magick)
ps_gif <- animate(ps,,width = 720, height = 480)
pc_gif <- animate(pc, width = 360, height = 480)
% k, @2 J) N2 `7 L; d- D# x3 ]ps_gifs <- image_read(ps_gif)
4 S/ I+ D" _0 L' z. L! Kpc_gifs <- image_read(pc_gif)
new_gif <- image_append(c(pc_gifs[1], ps_gifs[1]))
for(i in 2:length(pc_gifs)){
% N4 J+ h  ~* |: k$ t1 U  combined <- image_append(c(pc_gifs, ps_gifs))
: H1 l) O: G! o& w  new_gif <- c(new_gif, combined)
  Y" a7 K3 o7 A1 Y. z4 s. [}
- J$ w& [. J9 C, M" Knew_gif
/ A6 O9 x  n. f5 q0 T. w, G结果展示



3 A) E4 r: [; X- l8 C+ m

sjlxdn

111111111111