dplyrTut.R

library(gapminder)
library(tidyverse)

gapminder %<>% # note the reassignment...
  select(country, year, continent, lifeExp) %>%
  group_by(continent, country) %>%
  mutate(le_delta = lifeExp - lag(lifeExp)) %>%
  summarize(worst_le_delta = min(le_delta, na.rm = TRUE)) %>%
  arrange(worst_le_delta) %>%
  head(5)

# Arrange factors for an ordered plot:
gapminder$country <- factor(gapminder$country, levels = gapminder$country[order(gapminder$worst_le_delta)])

ggplot(data = gapminder, aes(country, worst_le_delta, fill = worst_le_delta)) +
  geom_bar(stat = "identity") + 
  guides(fill = FALSE) +
  labs(y = "Change in Life Expectancy (years)",
       x = "Country",
       caption = "Data from Gapminder",
       title = "Greatest negative change in life expectancy",
       subtitle = "All countries are located in Africa..."
       ) +
  theme_bw()