Nations GDP

Nations Dataset

library(tidyverse)

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── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
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ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

setwd("/Users/Lucinda/Downloads/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.

Use mutate to make a new GDP column

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

Chart 1: dplyr commands

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

Plot chart 1

ggplot(givencountries,
       aes(x = year,
           y = GDP,
           color = country)) +
  labs(title = "GDP in Trillions of $ by Country",
       x = "Year",
       y = "GDP") +
  geom_line() +
  geom_point() +
  scale_color_brewer(palette = "Set1") +
  theme_minimal()

Chart 2: dplyr commands

nations2 <- nations |>
  group_by(region, year) |>
  summarise(GDP = sum(GDP, na.rm = TRUE))

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

ggplot(nations2, aes(x=year, y=GDP, fill=region)) +
  geom_area(color = "white",
            lwd = 0.5,
            linetype = 1) +
  labs(x = "Year", y = "GDP",
       title = "GDP in Trillions of $ by Region") +
      scale_fill_brewer(palette = "Set2") +
  theme_minimal()