When there's a need to vow audiences with smart data analysis, there's invention.
Let's start with the U.S. home ownership data. The total occupied homes are subdivided into owner-occupied and renter-occupied. Thus, in any given year, we can compute the proportion of homes that are owner- or renter-occupied. We use blue for owner and red for renter, as follows:
Just to confirm, if we superimpose these two charts, we see that the proportions add up to 100%. One chart is the mirror image of the other:
Now we have confirmed the data is okay, we pull the charts apart. We change the scale of the renter chart so that the change over time is more clearly displayed. Since the home ownership bubble burst, it's the rental market that has grown.
It's time for some magic! We superimpose the charts again to obtain this:
[Ed: The remainder of the post below is modified from the original version based on reader comments]
The chart designer managed to make the two data series look different even though one series is the mirror image of the other.
The inspiration of this post came from reader Leanne C. who submitted this MSNBC chart:
Initially, I mistakenly assumed what is plotted are proportions. It just so happened that the total occupied units in the U.S. is in the 100M range and the owner v. rental are split 70M / 30M. I looked at the left end of the chart, and saw in 2001, about 33 of rental and about 69 of owner, which happens to add up to 100 (with rounding error). But if I had looked at right-end of the chart, where rental is 39 and owner is 75, then it would have been clear it's not adding up.
In any case, this chart looks different if we make the scales the same. In the following, each unit of both axes represents 2M units. There really is no justifiable reason why the scales should be different given that they both measure the same objects.
But using different ranges on each axis also presents a challenge: it is tempting to read meaning into the gaps between the two lines but these gaps merely reflect the choice of axis ranges.
Instead, we should convert all these units into growth indices. Let 100 be the year 2001 units. The following chart then shows what's really going on in housing:
Between 2001 and 2008, rental- and owner-occupied units experienced the same total growth (about 4%) although the trajectories were different... owner-occupied units went up steadily during this period while renter-occupied declined till 2004 and then experienced a faster growth rate between 2004-2008. Since 2008, renter-occupied continued about the same growth rate while owner-occupied flattened out and may be slightly declining.