Charts about U.S. rents and mortgages provide good examples of visualizing data. The topic might interest students who will likely rent but could consider buying a home someday. Depending the city, rent money put towards a mortgage could buy a lot or very little square footage. Here are a few charts from the NY Times and from the original source—data from Point2, a real estate analysis company, which provides a few visualizations and clear explanations.

List of Cities. In this NY Times chart, which is essentially a table, the winners and losers are clear in chronological order. But students might see better graphics: a line chart, horizontal bar, or vertical (column) bar chart might be too much with so many data points, but including fewer cities would work well. I’m also wanting to see percentages, which I often miss in data visualizations. In the Point2 article, you’ll see a bar chart within a table that’s a bit more visual.

Map. For a bigger picture, The Point2 article (not shown here) provides two U.S. maps with pinpoints showing the most affordable cities. Curiously, they present separate maps with most and least, and I wonder whether they could be combined, particularly to see the obvious geographic spread between eastern and western cities.

Tree Map. Shown here, this tree map is a great at-a-glance visual with mouseovers for more detail (see Point2 for the functionality). In addition to the proper sizing for each box, the designer added color to show in which cities you get the most space for the rent money.

Point2 makes the data practical by including insurance and property taxes. However, the researchers admit, “[W]e assumed a 20% down payment was covered.” Unfortunately, despite getting more space, buying instead of renting is still impossible for a lot of people. The article clarifies this obstacle and others. Overall, the article is a good example of presenting useful data for decision making.