Covid

library(readr)
library(ggplot2)
library(gganimate)
library(tidyverse)
library(ggrepel)
library(lubridate)
library(tidymodels)
library(modeltime)
library(tsbox)
library(TSstudio)
library(timetk)
library(tseries)

coviddat <- read_csv("owid-covid-data (4).csv")
coviddat$vax_perc<-(coviddat$people_fully_vaccinated/coviddat$population)*100
coviddat$week<-week(coviddat$date)

coviddat2<-coviddat%>%dplyr::select(date,
                                    week,
                                    location, 
                                    continent, 
                                    vax_perc,
                                    icu_patients_per_million, 
                                    stringency_index)%>%
  filter(continent=="Europe")%>%
  filter(complete.cases(.))%>%
  group_by(location)%>%
  summarise_by_time(date,.by="week",
                  vax_perc_week=max(vax_perc,na.rm=TRUE),
                  icu_week=max(icu_patients_per_million,na.rm=TRUE),
                  location=location,
                  continent=continent,
                  SI_week=mean(stringency_index,na.rm=TRUE))%>%distinct()
coviddat2$week<-week(coviddat2$date)
p<-coviddat2%>%filter(continent=="Europe" & 
                       date>"2020-12-31")%>%ggplot(., aes(
  x=vax_perc_week, 
  y=icu_week,
  size = SI_week, 
  color=as.factor(location),
  label=as.factor(location))) + 
  geom_text(nudge_y = 1) +
  ylim(0,120) +
  theme_bw() + 
  theme(legend.position = "none") +
  labs(title= 'Week: {closest_state}', 
       x = 'Fully Vaxed Percentage', 
       y = 'ICU patients per Million') +
  transition_states(week, 
                    transition_length = 2,
                    state_length = 1) +
  ease_aes('linear') + 
  enter_fade()+
  exit_fade()
anim <- animate(p,nframes=3500, fps=35)
anim2 <- animate(p,nframes=350, fps=3)
anim3 <- animate(p,nframes=350, fps=15)
anim4 <- animate(p,nframes=350)
anim_save(filename="VAX_ICU.gif", animation=anim4)