National data charts

library(dplyr)

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library(ggplot2)
library(tidyverse)

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setwd("/Users/precious/Downloads/DATASETS")

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
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nations <- nations %>%
  mutate(gdp = (gdp_percap * population) / 1e12)

chart1_data <- nations %>%
  filter(country %in% c("China", "Germany", "Japan", "United States"))

ggplot(chart1_data, aes(x = year, y = gdp, color = country)) +
  geom_point() +
  geom_line() +
  scale_color_brewer(palette = "Set1") +
  labs(
    title = "China's Rise to the Largest Economy",
    x = "year",
    y = "GDP ($ trillion)",
    color = NULL
  ) +
  theme_minimal()

chart2_data <- nations %>%
  group_by(region, year) %>%
  summarize(GDP = sum(gdp, na.rm = TRUE), .groups = "drop")

ggplot(chart2_data, aes(x = year, y = GDP, fill = region)) +
  geom_area(color = "white", linewidth = 0.2) +
  scale_fill_brewer(palette = "Set2") +
  labs(
    title = "GDP by World Bank Region",
    x = "year",
    y = "GDP ($ trillion)",
    fill = "region"
  ) +
  theme_minimal()