Dr. Drang's lifelong readers are well aware of his opinions on chart-making, especially his disdain for stacked area charts. For the record, I've generally agreed with Dr. Drang's criticisms, especially on charts with pseudo baselines—explicit or implied.
Not long ago, Dr. Drang poked Ben Evans in the eye over this issue after Ben tweeted a stacked area chart showing computer unit sales data. Ben predictably lashed back at Dr. Drang, as most people would after having the product of their livelihood called out in such an open place as Twitter.
In this instance, as an unemotional observer of this brief foodfight, I agree with Dr. Drang—or at least the spirit his argument (namely the pseudo baseline problem).
I have no reason to comment on this little spat other than to say it so perfectly snapshots the century-old debate on graphical deception.
In the introduction to Chapter Two, "Graphical Integrity," in his masterpiece The Visual Display of Quantitative Information, Edward Tufte deftly characterizes the tug-of-war in question:
For many people the first word that comes to mind when they think about statistical charts is "lie." No doubt some graphics do distort the underlying data, making it hard for the viewer to learn the truth. But data graphics are no different from words in this regard, for any means of communication can be used to deceive. There is no reason to believe that graphics are especially vulnerable to exploitation by liars; in fact, most of us have pretty good graphical lie detectors that help us see right through frauds.
Much of twentieth-century thinking about statistical graphics has been preoccupied with the question of how some amateurish chart might fool a naive viewer. Other important issues, such as the use of graphics for serious data analysis, were largely ignored. At the core of the preoccupation with deceptive graphics was the assumption that data graphics were mainly devices for showing the obvious to the ignorant. It is hard to imagine any doctrine more likely to stifle intellectual progress in a field. The assumption led down two fruitless paths in the graphically barren years from 1930 to 1970: First, that graphics had to be "alive," "communicatively dynamic," overdecorated and exaggerated (otherwise all the dullards in the audience would fall asleep in the face of those boring statistics). Second, that the main task of graphical analysis was to detect and denounce deception (the dullards could not protect themselves).
With these words, Tufte equitably distributes the responsibility for visual truth-telling on the graphic's creator and its audience. The lesser the weight of evil intentions on one side of the scale, the smaller the moral heft required of the other. But neither side should ever be exonerated from their responsibility to transmit or translate the truth.
Tufte wraps up his introduction to Chapter 2 of the book by shifting his sermon back to the graphical creator, who is obviously his audience in the book:
Deception must always be confronted and demolished, even if lie detection is no longer at the forefront of research. Graphical excellence begins by telling the truth about the data.
And this is how we—that is, everyone in the world who has chosen or been chosen to communicate data through graphics—should go from here. All we can do is prioritize truth-telling. Our audience's reception of the truth will never be entirely within our control.
In many ways knowledge is a curse. But the more we know of the psychological traps of the human mind, the more responsibility we have not to lay them.