HW- Nations dataset

Set Libraries

library(tidyverse)
library(RColorBrewer)
library(plotly)

Import dataset

nations<- read_csv("nations.csv")

GDP of each country in trillions of dollars

nations_gdp <- nations |>
  mutate(gdp_trillions = gdp_percap*population/1000000000000)

Plot 1:

Filter the four countries

nations4<- nations_gdp|>
  filter(country %in% c("China",
                        "United States",
                        "Germany",
                        "Japan")
         )

p1<- ggplot(nations4, aes(year, gdp_trillions, color = country)) +
  geom_point() +
  geom_line() + 
  scale_color_brewer(palette = "Set1") +
  labs(title = "China's Rise to Become the Largest Economy")+
  scale_x_continuous(name = "Year") +
  scale_y_continuous(name = "GDP (Trillions of $)")+
  theme_minimal()

p1

Interactive Plot 1

ggplotly(p1)

Set the dataset

region_data <- nations_gdp |>
  group_by(region, year) |>
  summarise(sum_GDP = sum(gdp_trillions, na.rm = TRUE))

Plot 2

p2 <- ggplot(region_data, aes(year, sum_GDP, fill = region)) +
  geom_area(color = "white", #very thin white line around each area
            linewidth = 0.1) +
  scale_fill_brewer(palette = "Set2") +
  theme_minimal() +
  labs(title = "GDP by World Bank Region") +
  scale_x_continuous(name = "Year") +
  scale_y_continuous(name = "GDP ($ Trillion)")
#If you needed to angle the lables on x-axis, use 
#theme(axis.text.x = element_text(angle = 45, hjust = 1))

p2

Interactive Plot 2

ggplotly(p2)