Chapter 26 18. Example Solutions for Extra Practice

26.1 18.1 Titanic: Survival Count by Sex

titanic %>%
  count(Sex, Survived) %>%
  ggplot(aes(x = Sex, y = n, fill = Survived)) +
  geom_col(position = "dodge") +
  labs(
    title = "Titanic Survival Count by Sex",
    x = "Sex",
    y = "Number of Passengers",
    fill = "Survived"
  )

26.2 18.2 WHO: Total Cases by Sex

who_clean %>%
  group_by(sex) %>%
  summarize(total_cases = sum(cases, na.rm = TRUE)) %>%
  arrange(desc(total_cases))

## # A tibble: 2 x 2
##   sex   total_cases
##   <chr>       <dbl>
## 1 m        27490494
## 2 f        15907024

26.3 18.3 WHO: Total Cases by Age Group

who_clean %>%
  group_by(age) %>%
  summarize(total_cases = sum(cases, na.rm = TRUE)) %>%
  arrange(desc(total_cases)) %>%
  ggplot(aes(x = reorder(age, total_cases), y = total_cases)) +
  geom_col() +
  coord_flip() +
  labs(
    title = "Total TB Cases by Age Group",
    x = "Age Group",
    y = "Total Cases"
  )