require(tidyverse) # The tidyverse package covered last time 

# install.packages("ggthemes")
require(ggthemes) # for great visualization colors and themes. 

# install.packages("maps")
require(maps) # for some maps data

# Gapminder data (for example)


The Gapminder dataset is a famous dataset used by Hans Rosling to visualize development outcomes. The data covers 1952 to 2007 in five year intervals and measures life expectancy, population, and GDP Per Capita.

gapminder %>% head()

Get to know the data through visualization

Each of the following questions are targeted at making sure we understand our data better. A great way to get a “feel” for a dataset is to visualize it. Answer each of the below questions with a (publishable-quality) picture.

1. How is lifeExp, pop and gdpPercap variables distributed?

Two ways to think about this: one is to plot each figure individually.

# Life Expectancy
gapminder %>% 
  ggplot(aes(lifeExp)) +
  geom_histogram(bins=30) +

# Population
gapminder %>% 
  ggplot(aes(pop)) +
  geom_histogram(bins=30) +