Data 110 HW5

library(tidyverse)

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

setwd("~/Data 110 101")
nations <- read.csv("nations.csv")

Plot 1:

nations2 <- nations |>
  mutate(tri_gdp = (gdp_percap*population)/1000000000000) |>
  filter(country == "China" | country == "Germany" | country == "Japan" | country == "United States")

p1 <- ggplot(nations2, aes(year, tri_gdp, color = country)) +
  geom_point() +
  geom_line() + 
  scale_color_brewer(palette = "Set1") +
  theme_minimal() +
  labs(
    title = "China's Rise to Become the Largest Economy",
    color = "Country"
  ) +
  scale_x_continuous(name = "Year") +
  scale_y_continuous(name = "GDP (Trillions of $)"); p1

Interactive Plot 1:

library(plotly)

Warning: package 'plotly' was built under R version 4.4.3

Attaching package: 'plotly'

The following object is masked from 'package:ggplot2':

    last_plot

The following object is masked from 'package:stats':

    filter

The following object is masked from 'package:graphics':

    layout

ggplotly(p1)

Plot 2:

nations3 <- nations |>
  mutate(tri_gdp = (gdp_percap*population)/1000000000000) |>
  group_by(region, year) |>
  summarise(gdp_sum = sum(tri_gdp, na.rm = TRUE))

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

p2 <- ggplot(nations3, aes(year, gdp_sum, fill = region)) +
  geom_area(color = "white", linewidth = 0.1) +
  scale_fill_brewer(palette = "Set2") +
  theme_minimal() +
  labs(
    title = "GDP by World Bank Region",
    fill = "Region"
  ) +
  scale_x_continuous(name = "Year") +
  scale_y_continuous(name = "GDP ($ Trillion)"); p2

Interactive Plot 2:

ggplotly(p2)