Nations Dataset

setwd("~/Desktop/RWD")
nations <- read.csv("nations.csv")
library(tidyverse)

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nations <- mutate(nations, gdp = gdp_percap * population / 10^12)

filter_nations <- nations %>%
  filter(country %in% c("Japan", "Germany", "China", "United States")) 

ggplot(filter_nations, aes(x = year, y = gdp, color = country)) +
  geom_point() +
  geom_line() +
  scale_color_brewer(palette = "Set1") +
  ggtitle("China's Rise To Becoming The Biggest Economy") +
  xlab("Year") +
  ylab("GDP (trillions of dollars)")

nations2 <- nations %>% 
  group_by(region, year) %>% 
  summarise(gdp = sum(gdp, na.rm = TRUE))

## `summarise()` has grouped output by 'region'. You can override using the
## `.groups` argument.

ggplot(nations2, aes(x = year, y = gdp, fill  = region)) +
  geom_area (color = "white", linewidth = 0.2) + 
  scale_fill_brewer(palette = "Set2") +
  ggtitle("GDP by World Bank Region") +
   xlab("Year") +
  ylab("GDP (trillions of dollars")