2.2 Fuel economy data

In this chapter, we’ll mostly use one data set that’s bundled with ggplot2: mpg. It includes information about the fuel economy of popular car models in 1999 and 2008, collected by the US Environmental Protection Agency, http://fueleconomy.gov. You can access the data by loading ggplot2:

#> # A tibble: 234 x 11
#>   manufacturer model displ  year   cyl trans      drv     cty   hwy fl    class 
#>   <chr>        <chr> <dbl> <int> <int> <chr>      <chr> <int> <int> <chr> <chr> 
#> 1 audi         a4      1.8  1999     4 auto(l5)   f        18    29 p     compa…
#> 2 audi         a4      1.8  1999     4 manual(m5) f        21    29 p     compa…
#> 3 audi         a4      2    2008     4 manual(m6) f        20    31 p     compa…
#> 4 audi         a4      2    2008     4 auto(av)   f        21    30 p     compa…
#> 5 audi         a4      2.8  1999     6 auto(l5)   f        16    26 p     compa…
#> 6 audi         a4      2.8  1999     6 manual(m5) f        18    26 p     compa…
#> # … with 228 more rows

The variables are mostly self-explanatory:

  • cty and hwy record miles per gallon (mpg) for city and highway driving.

  • displ is the engine displacement in litres.

  • drv is the drivetrain: front wheel (f), rear wheel (r) or four wheel (4).

  • model is the model of car. There are 38 models, selected because they had a new edition every year between 1999 and 2008.

  • class is a categorical variable describing the “type” of car: two seater, SUV, compact, etc.

This dataset suggests many interesting questions. How are engine size and fuel economy related? Do certain manufacturers care more about fuel economy than others? Has fuel economy improved in the last ten years? We will try to answer some of these questions, and in the process learn how to create some basic plots with ggplot2.

2.2.1 Exercises

  1. List five functions that you could use to get more information about the mpg dataset.

  2. How can you find out what other datasets are included with ggplot2?

  3. Apart from the US, most countries use fuel consumption (fuel consumed over fixed distance) rather than fuel economy (distance travelled with fixed amount of fuel). How could you convert cty and hwy into the European standard of l/100km?

  4. Which manufacturer has the most models in this dataset? Which model has the most variations? Does your answer change if you remove the redundant specification of drive train (e.g. “pathfinder 4wd”, “a4 quattro”) from the model name?