September 29 2022

## Agenda

• Case studies:
• Artists in the USA

## Data

We will be working with data on Artists in the USA.

More specifically, we will be building a visualization on aggregate data based on the original data set.

Discuss with a classmate(s) which variables you’d map to what elements in your plot. You can draft it out on paper (that’s often very helpful).

## Starting out

4. Do any data transformations (sorting, filtering, etc.) that you deem necessary

## Visualizing two categorical variables

For dealing with multiple categorical variables, we can add color to encode one of our variables.

We can use the stack transform to generate different y2/x2 values.

transform: [
{
type: "stack",
groupby: ["type"],
field: "percent",
as: ["x0", "x1"],
sort: { field: "race" }
}

## Update your spec

1. Add a color scale (if you haven’t already) for the field race
2. Use the newly created variables (x0 and x1) in your marks spec
3. Sort the bars so we can make sense of the proportions (which variable should you sort by?)
4. Add a legend and titles