gapminderScatterPlots.r

# load and inspect gapminder data
library(dslabs)
data(gapminder)
head(gapminder)

# compare infant mortality in Sri Lanka and Turkey
gapminder %>%
    filter(year == 2015 & country %in% c("Sri Lanka", "Turkey")) %>%
    select(country, infant_mortality)
    
# basic scatterplot of life expectancy versus fertility
ds_theme_set()    # set plot theme
filter(gapminder, year == 1962) %>%
    ggplot(aes(fertility, life_expectancy)) +
    geom_point()

# add color as continent
filter(gapminder, year == 1962) %>%
    ggplot(aes(fertility, life_expectancy, color = continent)) +
    geom_point()
    
#Faceting makes multiple side-by-side plots stratified by some variable. This is a way to ease comparisons.

# facet by continent and year
filter(gapminder, year %in% c(1962, 2012)) %>%
    ggplot(aes(fertility, life_expectancy, col = continent)) +
    geom_point() +
    facet_grid(continent ~ year)

# facet by year only
filter(gapminder, year %in% c(1962, 2012)) %>%
    ggplot(aes(fertility, life_expectancy, col = continent)) +
    geom_point() +
    facet_grid(. ~ year)

# facet by year, plots wrapped onto multiple rows
years <- c(1962, 1980, 1990, 2000, 2012)
continents <- c("Europe", "Asia")
gapminder %>%
    filter(year %in% years & continent %in% continents) %>%
    ggplot(aes(fertility, life_expectancy, col = continent)) +
    geom_point() +
    facet_wrap(~year)