HW-Nations

Nations HW

load tidyverse and the nations dataset.

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   3.5.1     ✔ 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

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.

create new variable for gdp

nations <- nations|>mutate(gdp_tril= gdp_percap*population/10^12)

filter for the 4 selected countries and plot 1

#plot 1
n1 <- nations|>filter(country %in% c("China", "Germany", "Japan", "United States"))
p1 <- ggplot(n1, aes(x=year, y=gdp_tril, color=country)) +
  geom_point() + geom_line() +
  scale_color_brewer(palette = "Set1") +
  theme_minimal() +
  labs(x="year", y="GDP ($trillion)", color = element_blank(), caption="World Bank Data", 
       title="China's Rise to Become the Largest Economy")
p1

regroup and summarize data by region and plot 2

#plot 2
n2 <- nations|>group_by(region, year)|> summarise(gdp = sum(gdp_tril, na.rm=T))

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

p2 <- ggplot(n2, aes(x=year, y=gdp, fill=region)) +
  geom_area(color="white") +
  scale_fill_brewer(palette = "Set2") +
  theme_minimal() +
  labs(x="year", y="GDP ($trillion)", caption="World Bank Data", 
       title="GDP by World Bank Region")
p2