Nations

library(tidyverse)

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✔ lubridate 1.9.4     ✔ tidyr     1.3.1
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── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
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library(RColorBrewer)
setwd("~/Library/Mobile Documents/com~apple~CloudDocs/Data110")
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.

head(nations)

# A tibble: 6 × 10
  iso2c iso3c country  year gdp_percap population birth_rate neonat_mortal_rate
  <chr> <chr> <chr>   <dbl>      <dbl>      <dbl>      <dbl>              <dbl>
1 AD    AND   Andorra  1996         NA      64291       10.9                2.8
2 AD    AND   Andorra  1994         NA      62707       10.9                3.2
3 AD    AND   Andorra  2003         NA      74783       10.3                2  
4 AD    AND   Andorra  1990         NA      54511       11.9                4.3
5 AD    AND   Andorra  2009         NA      85474        9.9                1.7
6 AD    AND   Andorra  2011         NA      82326       NA                  1.6
# ℹ 2 more variables: region <chr>, income <chr>

nations1 <- nations |>
  mutate(gdp=gdp_percap*population/10^12) |>
  filter(country %in% c("China", "Nigeria", "United States", "Germany"))

ggplot(data=nations1, aes(x=year, y=gdp, color=country))+
  geom_line()+ 
  geom_point()+
  scale_color_brewer(palette = "Set1")+
  theme_minimal(base_size = 14)+
  labs(title="United States and China Compete in Economic Rise", 
     x="Year", 
     y="GDP (Dollars/Trillion)")

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.

ggplot(data=nations2, aes(x=year, y=GDP, fill=region))+
  geom_area(color="navy")+
  theme_minimal(base_size = 14)+
  scale_fill_brewer(palette = "PiYG")+
  labs(title="GDP per Trillion Dollars Each Year for Global Regions", 
       x="Year", 
       y="GDP per Trillion Dollars")