Assignment 9

Submission: Submit the link on Github of the assignment to Blackboard.

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1. Use the dataset by of covid 19 by WHO at https://covid19.who.int/WHO-COVID-19-global-data.csv. Find the three countries with the most numbers of deaths by Covid-19.

Hint:

• Use filter to select the most current date

• Pipe with arrange(-Cumulative_deaths) to rank the data by the number of cumulative deaths

library(tidyverse)
df <- read_csv('https://covid19.who.int/WHO-COVID-19-global-data.csv')
df1 <- df %>% 
  filter(Date_reported == "2020-10-5") %>% 
  arrange(-Cumulative_deaths)
# The three countries with the highest cumulative deaths are the US, Brazil, and India.

2. Make a plot revealing the number of deaths in the three countries with the most numbers of deaths

library(gganimate)
df %>% 
  filter(Country %in% c("United States of America","Brazil","India")) %>% 
  ggplot(aes(x=Date_reported,y=New_deaths,color=Country)) + geom_line() +
  geom_point(size = 3) + transition_reveal(Date_reported) + 
  labs(x="Date",y="Deaths",title="Deaths over Time")

3. Create the new variable (column) death_per_cases recording the number of deaths per cases (Hint: divide cumulative deaths by cumulative cases). What are the three countries with the highest deaths per cases?

df2 <- df %>% 
  filter(Date_reported == "2020-10-5") %>% 
  mutate(death_per_cases = Cumulative_deaths/Cumulative_cases) %>% 
  arrange(-death_per_cases)
# The three countries with the highest death_per_cases as of 10-5-2020 are Yemen, Italy, and Mexico.

4. Make a plot revealing the number of deaths per cases of the US, Italy and Mexico.

df %>% 
  filter(Country %in% c("United States of America","Italy","Mexico")) %>% 
  mutate(death_per_cases = Cumulative_deaths/Cumulative_cases) %>%
  ggplot(aes(x=Date_reported,y=death_per_cases,color=Country)) + geom_line() +
  geom_point(size=3) + transition_reveal(Date_reported) +
  labs(x="Date",y="Deaths per Cases",title="Deaths per Cases over Time")