Nations Dataset

Author

Arif

library(tidyverse)

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setwd("/Users/arifjadji/Desktop/DATA110/DATA110 Datasets")

gdp <- read_csv(file = "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.

gdp1 <- mutate(gdp, GDP = ((gdp_percap * population)/1000000000000))

gdp2 <- filter(gdp1, country == "Switzerland" | country == "Canada" | country == "China" | country == "United States")
ggplot (gdp2, aes(x = year, y = GDP, color = country)) +
  ylab("GDP($ trillion)") +
  ggtitle("Four Chosen Country's Economy Outlooks") +
  geom_point() +
  geom_line() +
  scale_color_brewer(palette = 'Set1')

gdp3 <- gdp1 %>% 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(gdp3, aes(year, GDP)) +
         xlab("Year") + ylab("GDP($ trillion)") +
         scale_fill_brewer(palette = 'Set2') +
         ggtitle("GDP For Each Region") +
         geom_area(colour = "white", aes(fill = region))