Nations Charts Assignments

Author

Ayan Elmi

library(dplyr)
library(ggplot2)

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

Creating new variable, GDP for each country in trillions of dollars.

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

Filtering for East African

first_chart<-nations |>
  filter(country %in% c ("Kenya", "Somalia", "Uganda", "Tanzania"))

# I removed the warning message I got for cleanliness.
ggplot(first_chart, aes(x=year, y=gdp_in_trillions, color = country))+
geom_point()+
geom_line()+
scale_color_brewer(palette = "Set1")+
labs (title= "GDP Growth in East African Countries", x="Year", y="GDP($trillion)", color = "country")+
theme_minimal()

Grouping by region and year, then summarizing for chart 2

second_chart<- nations |>
  group_by(region, year)|>
  summarize(GDP = sum(gdp_in_trillions, na.rm = TRUE))

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

Plotting the second chart

ggplot(second_chart, aes(x=year, y=GDP, fill=region))+
  geom_area(color= "white", lwd=0.25)+
scale_fill_brewer(palette ="Set2")+
labs (title= "GDP by World Bank", x="Year", y="GDP($trillion)", fill = "region")+
theme_minimal()

citations:

https://r-charts.com/evolution/area-chart-ggplot2/ used this link for the white lines seperating the colours.