06-Final-exercise.Rmd

# Final Exercise

## Gapminder challenge

<a href="http://gitsense.github.io/images/wealth.gif"><img src="figures/wealth.gif" style="width: 700px;"/></a>

- Inspired by the late, great [Hans Rosling](https://www.youtube.com/watch?v=jbkSRLYSojo)


Install and load the [`gapminder` data package](https://github.com/jennybc/gapminder)

```{r, eval=FALSE, echo=TRUE, include=TRUE}
install.packages("gapminder")
library(gapminder)
gapminder
```


Pick at least __two__ of the tasks below from the task menu and approach each with a table and figure. 

  * `dplyr` should be your main data manipulation tool
  * `ggplot2` should be your main visualization tool

## Tasks menu {-}

* The mean life expectancy across all years for France?

* Get the maximum and minimum of GDP per capita for all continents.

* Look at the spread of GDP per capita across countries within the continents.

* How does life expectancy vary across different continents? (Using a `ggplot`)




* Report the absolute and/or relative abundance of countries with low life expectancy over time by continent: Compute some measure of worldwide life expectancy - you decide - a mean or median or some other quantile or perhaps your current age. Then determine how many countries on each continent have a life expectancy less than this benchmark, for each year.

* Make up your own! 


---


You're encouraged to reflect on what was hard/easy, problems you solved, helpful tutorials you read, etc.


- Gapminder EDA ideas from [Jenny Bryan](http://stat545.com/hw03_dplyr-and-more-ggplot2.html), author and creator of the [Gapminder package](https://cran.r-project.org/web/packages/gapminder/index.html).