gistfile1.txt

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

getwd()
data_folder <- file.path("C:/Users/marcj/Nutreco/StatisticsPlatform/Website/ELearning/Workshops/CausalAnalysis/Covid/")
url <- "https://covid.ourworldindata.org/data/owid-covid-data.csv"
name <- "owid-covid-data.csv"
download.file(url = url, destfile = paste0(data_folder,name))
setwd(data_folder)
coviddat  <- read_csv(paste0(data_folder,name))
coviddat$vax_perc<-(coviddat$people_fully_vaccinated/coviddat$population)*100
coviddat$week<-week(coviddat$date)
coviddat$year<-year(coviddat$date)


data_folder <- file.path("")
url <- "https://data.rivm.nl/covid-19/COVID-19_varianten.csv"
name <- "COVID-19_varianten.csv"
download.file(url = url, destfile = paste0(data_folder,name))
setwd(data_folder)
variants  <- read_delim(paste0(data_folder,name),
                        delim = ";", escape_double = FALSE, trim_ws = TRUE)
coviddat2<-coviddat%>%dplyr::select(date,
                                    week,
                                    year,
                                    location, 
                                    continent, 
                                    vax_perc,
                                    icu_patients_per_million,
                                    excess_mortality,
                                    stringency_index)%>%
  filter(continent=="Europe")%>%
  filter(complete.cases(.))%>%
  group_by(location)%>%
  summarise_by_time(date,.by=c("week","year"),
                  vax_perc_week=max(vax_perc,na.rm=TRUE),
                  icu_week=max(icu_patients_per_million,na.rm=TRUE),
                  location=location,
                  continent=continent,
                  em_week=mean(excess_mortality,na.rm=TRUE),
                  SI_week=mean(stringency_index,na.rm=TRUE))%>%distinct()
coviddat2$week<-week(coviddat2$date)
coviddat2$year<-year(coviddat2$date)

my.animation<-coviddat2%>%filter(continent=="Europe" & 
                                   date>"2020-12-31")%>%
  ggplot(.)+
  geom_line(aes(x=date, 
                y=em_week, 
                colour=as.factor(location)))+
  geom_point(aes(x=date, 
                y=em_week, 
                colour=as.factor(location)), size=1)+
  geom_dl(aes(x=date, 
              y=em_week,
              label = location,
              colour=as.factor(location)), 
          method = list(dl.combine("last.points")), cex = 0.8) +
  theme_bw()+
  theme(legend.position="none")+
  labs(x="Date", 
       y="Excess Mortality", 
       title="Excess Mortality over Time by Country using OWID data", 
       col="Country")+
  transition_reveal(date)
animate(my.animation, width=2000, height=1000, 
        res=150,
        end_pause = 60,
        nframes=300);anim_save("CovidEM.gif")