- Using the
`mpg`

data, create a scatterplot of the highway fuel efficiency and city fuel efficiency.

- Now add a dashed reference line showing equivalent values for the two axes and set the aspect ratio to 1.

- Looks like there is a possibility of overplotting. Turn this into a bubble chart with dot size scaling to the number of data points for each dot and make the dot colors
*steelblue*.

- Add rugs to scatterplot #1 and change to minimal theme.

- From scatterplot #1, color the dots by class, move the legend to the top left corner of the plot, and add marginal density plots.

- Create a data frame called
`mpg_num`

that only includes variables with numeric values using the `where()`

function. Then remove the *year* column.

- Create correlation plots of the numeric variables in
`mpg_num`

in both base R and using {GGally}’s `ggpairs()`

function.

- Create a correlation matrix of
`mpg_num`

with the `cor()`

function. Then use `ggcorrplot()`

from the {ggcorrplot} package to make a heatmap correlation plot with just the upper triangle of the matrix and using circles to represent correlation coefficient magnitude.