Lab2

Graphic 1: Population in Southeast Asia from 1952 to 2002

SEA is a region dear to my heart so I chose to subset and filter the data to just focus on SEA countries. Since 1952 to 2002 is a period of time where there was a lot of peril in Southeast Asia, I wondered if this had an effect on population, life expectancy and GDP.

# Prepare data
seac <- c("Cambodia", "Thailand", "Singapore", "Vietnam", "Philippines", "Myanmar",
          "Malaysia", "Indonesia") 

sea <- gapminder %>% 
  filter(year > 1951 & year < 2005 & country %in% seac
         )
seapop <- ggplot(data = sea, aes(x = year, y = pop, color = country)) +
    geom_point() +
    xlab("Year") + ylab("Population") +
    ggtitle("Population over time for Southeast Asian Countries") + 
    scale_color_manual(name = "SEA nations",
                       values = c("Cambodia" = "#2ca25f", "Indonesia" = "#8856a7", 
                                  "Malaysia" = "#2b8cbe", "Myanmar" = "#feb24c", 
                                  "Philippines" = "#c994c7", "Singapore" = "#dd1c77", 
                                  "Thailand" = "#999999", "Vietnam" = "#5ab4ac" )) +
    theme_bw()

seapop    

ggsave("SEA populations.pdf", plot = seapop, height = 3, width = 5, units = "in")

Graphic 2: GDP per capita in Southeast Asia from 1950 to early 2000s

For Southeast asian nations, I used log scales to show the growth in GDP over time. I used a smooth curve to model the growth, instead of straight lines. The gray bar around it shows confidence intevals. While all the countries were experiencing GDP growth at relatively constant rates that time, it is interesting that the Philippines sincethe 1980s has experienced slower growth in relation to other countries.

seagdp <- ggplot(data = sea, aes(x = year, y = gdpPercap, color = country)) +
    geom_smooth() +
    xlab("Year") + ylab("GDP") +
    ggtitle("GDP over time for Southeast Asian Countries") + 
    scale_y_log10() +
    scale_color_manual(name = "SEA nations",
                       values = c("Cambodia" = "#2ca25f", "Indonesia" = "#8856a7", 
                                  "Malaysia" = "#2b8cbe", "Myanmar" = "#feb24c", 
                                  "Philippines" = "#c994c7", "Singapore" = "#dd1c77", 
                                  "Thailand" = "#999999", "Vietnam" = "#5ab4ac")) +
    xlim(1950,2015) +
    geom_dl(aes(label = country), cex = 0.5, method = list(dl.trans(x = x + .3), 
                                                           "last.bumpup")) +
    theme_classic() 
    
seagdp

## `geom_smooth()` using method = 'loess'