Exercise

# Visualizing many variables

As you begin to consider more variables, plotting them all at the same time becomes increasingly difficult. In addition to using x and y scales for two numeric variables, you can use color for a third numeric variable, and you can use faceting for categorical variables. And that's about your limit before the plots become to difficult to interpret. There are some specialist plot types like correlation heatmaps and parallel coordinates plots that will handle more variables, but they give you much less information about each variable, and they aren't great for visualizing model predictions.

Here's you'll push the limits of the scatter plot by showing the house price, the distance to the MRT station, the number of nearby convenience stores, and the house age, all together in one plot.

`taiwan_real_estate`

is available; `ggplot2`

is loaded.

Instructions

**100 XP**

- Using the
`taiwan_real_estate`

dataset, draw a scatter plot of`n_convenience`

versus the square root of`dist_to_mrt_m`

, colored by`price_twd_msq`

. - Use the continuous viridis plasma color scale.
- Facet the plot, wrapping by
`house_age_years`

.