Nations Assignment

Loaded in the necessary - libraries tidyverse, dplyr, ggplot2

library(tidyverse)

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✔ lubridate 1.9.3     ✔ tidyr     1.3.1
✔ purrr     1.0.2     
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library(dplyr)

library(ggplot2)

Imported “nations” data set using the read function

nations <- read.csv("nations.csv")

Originally used 1,000,000,000,000 which gave very large values for the y-axis, I was able to figure out how to change the values using 10^12 through the help of ChatGPT

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

Selected four countries and filtered them - I chose to compare four countries within the Middle East

middleeast <- nations_mut |>
  filter(country %in% c("Iran, Islamic Rep.", "Iraq", "Jordan", "Turkey")) 

Created the first plot

plot1 <- ggplot(middleeast, aes(x = year, y = gdp, color = country)) +
  geom_line(alpha = 0.3) + 
  geom_point() + 
  scale_color_brewer(palette = "Set1") +
  labs(title = "GDP In Middle Eastern Countries Over The Years",
       x = "Year",
       y = "GDP (trillions of dollars)")

plot1

Got “summarise() has grouped output by ‘region’. You can override using the .groups argument.” as a message and decided to research the argument which led me to stackoverflow where I was able to figure out how to use it.

summarize <- nations_mut |>
  group_by(region, year) |> 
  summarize(sum_gdp = sum(gdp, na.rm = TRUE), .groups = "drop")

Created the second plot

plot2 <- ggplot(summarize, aes(x = year, y = sum_gdp, fill = region)) +
  geom_area(color = "white") +
  scale_fill_brewer(palette = "Set2") +
  labs(title = "GDP In Different Regions Over The Years",
       x = "Year",
       y = "GDP (trillions of dollars)")
plot2