1. To transform spatial data from a shapefile to TopoJSON, I used the mapshaper.org site. I placed the .shp, .prj, .shx and .dbf files of my data into the site. Then, I clicked export for the file and chose the TopoJSON file format to export.

2. The difference between TopoJSON and GeoJSON is that TopoJSON is much smaller than GeoJSON due to having shared arcs, which allows for less redundancy. GeoJSON is used for geographic data such as points, lines, and polygons, and TopoJSON also does that. GeoJSONs have lists of features, and latitudes and longitudes to describe the geometry. TopoJSON describes the topologys of groups of features.

3. To upload and read TopoJSON or GeoJSON files into ObservableHQ, you start with clicking the paperclip icon. You can select the files from your computer and add them into your Observable HQ document from there. Loading the data and then converting specific things to GeoJSON allows you to read the file. Typing in file attachment and including the file.json enables you to load and read the file.

4. To upload and read CSV files into ObservableHQ, you first open the paperclip icon, and import your CSV file into the document. Then, putting the csv file into a file attachment, ObservableHQ will read and parse the data. You can choose certain variables to be included in your code by putting in their label, which will allow certain values to be pulled from the csv and into your code. For example, to show percentage of adults with depression in a county, I looked in the csv file for the header for that column, Per_Adults, and I wrote that into my csv parse.

5. To create a new variable from existing variables, you can calculate data from within the cell. For example, you can divide values from the table, like the number of minorities in a county divided by the total population of that county. That can give you new data in the form of the percentage of minorities in a certain county. Normalization is very important because it converts raw numbers into a standard scale, which allows for data to be comparable. It can allow for accurate ratios and more fairly represented data.