Nations Data Set

library(ggplot2)
library(dplyr)
library(highcharter)

## Warning: package 'highcharter' was built under R version 4.3.1

library(RColorBrewer)
library(tidyverse)

## Warning: package 'tidyr' was built under R version 4.3.1

library(scales)

## Warning: package 'scales' was built under R version 4.3.1

setwd ("C:\\Users\\asing\\Desktop\\data_science\\data_110\\week_4")
nations <- read_csv("nations.csv")

nations2 <- mutate(nations,gdp_tn = gdp_percap*population/10^12)

Check the headings of the data set

head(nations2)

## # A tibble: 6 × 11
##   iso2c iso3c country  year gdp_percap population birth_rate neonat_mortal_rate
##   <chr> <chr> <chr>   <dbl>      <dbl>      <dbl>      <dbl>              <dbl>
## 1 AD    AND   Andorra  1996         NA      64291       10.9                2.8
## 2 AD    AND   Andorra  1994         NA      62707       10.9                3.2
## 3 AD    AND   Andorra  2003         NA      74783       10.3                2  
## 4 AD    AND   Andorra  1990         NA      54511       11.9                4.3
## 5 AD    AND   Andorra  2009         NA      85474        9.9                1.7
## 6 AD    AND   Andorra  2011         NA      82326       NA                  1.6
## # ℹ 3 more variables: region <chr>, income <chr>, gdp_tn <dbl>

#View(nations)

Filtering the data set and getting BRICS which is Brazil, Russia, India, China, and South Africa

big5 <- nations2 %>% 
  filter(iso3c == "BRA" | iso3c == "RUS" | iso3c == "IND" | iso3c == "CHN" | iso3c == "ZAF") %>% 
  arrange(year)

Graphing BRICS Nations by GGPLOT

ggplot(big5, aes(x= year, y = gdp_tn, color = country))+
  theme_minimal(base_size = 15)+
  labs(title= "BRICS NATIONS")+
    xlab("Years") +
    ylab("GDP ($ Trillion)")+
    geom_point()+
    geom_line()+
      scale_color_brewer(palette = "Set1")

Prepareing Data for Second Graph

gdpworldbank <- nations2 %>% group_by(region,year) %>% summarize(gdp_tn = sum(gdp_tn, na.rm = TRUE))

Lets check the Data

head(gdpworldbank)

## # A tibble: 6 × 3
## # Groups:   region [1]
##   region               year gdp_tn
##   <chr>               <dbl>  <dbl>
## 1 East Asia & Pacific  1990   5.52
## 2 East Asia & Pacific  1991   6.03
## 3 East Asia & Pacific  1992   6.50
## 4 East Asia & Pacific  1993   7.04
## 5 East Asia & Pacific  1994   7.64
## 6 East Asia & Pacific  1995   8.29

Graphing the Data by Region using GGPLOT

p4 <- ggplot(gdpworldbank, aes(x = year, y = gdp_tn)) +
  geom_area(aes(fill = region), color = "white") +
  xlab("Year") +
  ylab("GDP ($ Trillion)") +
  theme_minimal(base_size = 15) +
  scale_fill_brewer(palette = "Set2")
p4