## Adding more plot aesthetics

In their most basic form scatter plots can only visualize datasets in two dimensions through the `x`

and `y`

aesthetics of the `geom_point()`

layer. However, most data sets have more than two variables and thus might require additional plotting dimensions. `ggplot()`

makes it very easy to map additional variables to different plotting aesthetics like `size`

, transparency `alpha`

and `color`

.

Let’s consider the `gapminder_2007`

dataset which contains the variables GDP per capita `gdpPercap`

and life expectancy `lifeExp`

for 142 countries in the year 2007:

ggplot(gapminder_2007) + geom_point(aes(x = gdpPercap, y = lifeExp))

Mapping the `continent`

variable through the point `color`

aesthetic and the population `pop`

(in millions) through the point `size`

we obtain a much richer plot including 4 different variables from the data set: