When it comes to space or time in graphics, old habits die hard. When we have spatial data, the default is to put it on a map. When we have a time series, the default is to plot time along the horizontal axis. Sometimes, these defaults work; other times, breaking up the map or straight-time-line works better.
Thanks to a reader, I noticed that Google put up a "Flu Trends" website to help us track the flu season. They use two main charts to plot the data, as shown below.
On the right side is the time series, showing the severity of flu cases from month to month. There are many great things about this chart and one serious flaw. I love the fact that they did not plot time on the horizontal axis; they realize the seasonality and they create overlapping lines. They make good use of foreground and background; it's easy for us to compare year to year differences.
The serious flaw: no vertical scale. This was a problem with Google Trends from day one (see my post here). They still haven't fixed it. Because of this, we don't know if the peak shown was 5 cases or 5000 cases. While for Google key word searches, one can excuse them for trying to protect commercial secrets. I would imagine that this public health data is, well, public. Since the apparent purpose of this chart is to allow citizens to declare a flu epidemic (say, when they see the current trend depart from the historical norm), not having the scale is a huge problem.
I also disagree with shifting the months around for the Northern Hemisphere so that the peaks of the graphs are aligned towards the middle. It is better for the peaks to appear on the left and let the order of the months conform to our expectation. (The "peak" would be split on the sides and the chart would look like a valley, which presumably is why they did it this way.)
The charts on the left side plot the spatial data, not surprisingly on maps. Sadly, the standard exhibited on the time-series charts is nowhere found on these maps.
First, the legend is seriously deficient.
This poorly aggregated map becomes a farce when applied to the U.S. There is not much left to be said, is there?