You Should Have Bought That Condo in 2012 and You Should Have Bought It in Oakland, Plus Other Findings About U.S. Home Value Over the Past Four Years

This growth is not evenly distributed. Florida, Michigan, and the West have benefited the most.

Growth in housing value across states. Darker green means higher growth rate. For an interaction version of this chart, see here: https://public.tableau.com/shared/MGY2B4HRC?:display_count=yes.

The biggest winners of 2012–2016 are also the biggest winners of 2003–2007.

Correlation between a state’s home value growth rate in 2012–2016 and its growth rate in 2003–2007. For an interactive version of this chart, see here: https://public.tableau.com/views/property_value/2012-2016vs2003-2007growth?:embed=y&:display_count=yes.

The faster a state is growing, the more unequal that growth is.

Correlation between a state’s median home value growth rate and the spread in growth rate among cities in that state. For an interactive version of this chart, see here: https://public.tableau.com/views/property_value/stategrowthvsinequality?:embed=y&:display_count=yes.

You think San Francisco’s housing market is out of control? Take a look at Oakland.

A box-and-whisker plot usually looks something like this image below. There are five horizontal lines in the chart (they would be vertical lines if the plots are rotated 90 degrees as they sometimes are).

The line at the very top represents the maximum value in the dataset. Imagine, for example, that we have a dataset with the current age of the Backstreet Boys — 42 (for Howie), 36 (for Nick), 44 (for Kevin), 41 (for Brian), and 38 (for A.J.). In this example, the maximum value would be 44. Kevin has come a long way from his boy band days. The line at the very bottom represents the minimum value, so that would be 36 in our Backstreet Boys example.

To figure out the value for the other three lines, we need to rearrange the Boys’ ages in order, so something like 36, 38, 41, 42, 44. Then, the median is the value that’s in the middle or halfway from either end of the dataset (so 41 in this case), the 1st Quartile is the value that’s one-fourth of the way from the smallest item in the dataset (so the 1st Quartile would be 38 in this case), and the 3rd Quartile is the value that’s one-fourth of the way from the largest item in the dataset (so the 3rd Quartile would be 42 in our example).

So in one chart, you’re able to see the max, min, and median, plus you get a visual sense of the spread between max and min and where most of the items in the dataset fall between max and min. Pretty powerful stuff.

That’s my attempt to show you the meaning of being box-and-whiskered. But now it’s time to quit playing games with my post and get back to the subject at hand.

2012–2016 home value growth rates in seven different cities. For an interactive version of this chart, please see: https://public.tableau.com/views/property_value/cities-boxwhisker?:embed=y&:display_count=yes.

Takeaways, recommendations, further exploration, learnings

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