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@cavedave
Created October 2, 2021 10:29
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Do high trust countries have higher covid vaccination rates? Data from ourworldindata
trust <- read.csv("self-reported-trust-attitudes.csv",header=TRUE)
library(dplyr)
trust <- trust %>%
group_by(Entity) %>%
filter(Year == max(Year))
vac <- read.csv("owid-covid-data (1).csv",header=TRUE)
vac<-vac %>%
dplyr::select(people_vaccinated_per_hundred, location, date)
library(lubridate)
vac$date<-ymd(vac$date)
vac<-na.omit(vac)
vac2 <- vac %>%
group_by(location) %>%
filter(people_vaccinated_per_hundred == max(people_vaccinated_per_hundred))
#merge two datasets
joined_df <- merge(trust, vac2, by.x = "Entity",
by.y = "location", all.x = TRUE, all.y = FALSE)
joined_df<-rename(joined_df, Trust = Trust.in.others..World.Values.Survey..2014..)
joined_df<-rename(joined_df, Vaccinated = people_vaccinated_per_hundred)
#look for intereting countries
filter(joined_df, Trust > 65)
find<-dplyr::filter(joined_df, grepl("Armenia",Entity))
#find blank entry and remove it
new_DF <- joined_df[rowSums(is.na(joined_df)) > 0,]
new_DF
joined_df = joined_df[-c(70),]
#get correltation
res <- cor(joined_df$Vaccinated,joined_df$Trust)
#graph
library(ggplot2)
p<-ggplot(joined_df, aes(x=Vaccinated, y=Trust)) + geom_point()+ geom_smooth(method="auto", se=TRUE, fullrange=FALSE, level=0.95)
p<-p + ggtitle("Countries Covid Vaccination Rates") +
xlab("% Vaccinated") + ylab("Trust") +theme_bw()+ theme(plot.title = element_text(hjust = 0.5))
#add in labels
q<-p + annotate(geom="text", x=73, y=76, label="Norway",
color="black",size = 3.5)
q<-q + annotate(geom="text", x=60, y=40, label="USA",
color="black",size = 3.5)
q<-q + annotate(geom="text", x=71, y=28, label="UK",
color="black",size = 3.5)
q<-q + annotate(geom="text", x=70, y=0, label="data:ourworldindata\n cor:.45",
color="black",size = 2.5)
ggsave("TrustVaccines.png")
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cavedave commented Oct 2, 2021

TrustVaccines

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