Nations

library(tidyverse)

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.5
✔ forcats   1.0.0     ✔ stringr   1.5.1
✔ ggplot2   3.4.4     ✔ tibble    3.2.1
✔ lubridate 1.9.3     ✔ tidyr     1.3.1
✔ purrr     1.0.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(dplyr)
library(ggplot2)
library(RColorBrewer)

setwd("/Users/kevinsanchez/Downloads")
nations <- read_csv("nations.csv")

Rows: 5275 Columns: 10
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (5): iso2c, iso3c, country, region, income
dbl (5): year, gdp_percap, population, birth_rate, neonat_mortal_rate

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

nations_ds <- nations |>
  mutate(GDP = (nations$gdp_percap * nations$population)/10^12) |>
  filter(country %in% c("China", "Germany", "United States", "Japan"))

chart1 <- ggplot(nations_ds, aes(x = year, y = GDP, color = country)) + 
  geom_point() +
  geom_line() +
scale_color_brewer(palette = "Set1") +
labs(title = "China's Rise to Become the Largest Economy",
       x = "Year", 
       y = "GDP (in $trillions)", 
       color = "Country")
chart1

new_nations2 <- nations |> 
  mutate(gdp = (gdp_percap*population)/10^12) |> 
  group_by(region, year) |> 
  summarize(gdp = sum(gdp, na.rm = TRUE)) 

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

chart2 <- ggplot(new_nations2, aes(x = year, y = gdp, fill = region)) +
  geom_area() + 
  scale_fill_brewer(palette = "Set2") + 
  labs(title = "GDP by World Bank Region")+ 
  xlab("Year")+
  ylab("Gross Domestic Product (trillions)")
chart2