James C @annelidworm sent me to this BBC chart, which he thinks is "hard on the eyes":
I find a few things I like, and also a few I don't.
Unlike James, I actually find the chart quite pretty. The use of a small-multiples to compare season tickets with single tickets is also nice. For someone like me, who isn't well versed in the British map, the geography lesson is appreciated - although for a local reader, this may be superfluous. The thickness of lines used to encode the data works alright.
There are a few problems with the chart:
There is a self-sufficiency problem. This is a chart in which every data element is printed on the chart, which means the graphical pieces are merely cosmetic. If the data labels were removed, the reader would be entirely lost. However, this problem can be solved by judicious use of colors.
Consider how color is used here. Blue and yellow distinguishes between season and single tickets but the small-multiples setup already does the job well enough. The tint is used in some arbitrary manner unrelated to the data, as far as I can tell.
Instead, price increases above the rate of inflation should be differentiated from price changes below the rate of inflation by using two colors. The special case of Birmingham's season ticket which increased exactly at the rate of inflation deserves its own color.
Speaking of increases relative to inflation. The analyst helpfully explains via the legend that any number above 66 percent is ahead of inflation, and any number below is behind inflation, meaning prices have actually come down. The entire dataset can be simplified by subtracting 66% from each number to show the "real" price changes.
Take a step back. What is the story in this dataset? The numbers on the right side are all much higher than those on the left, with Shoeburyness being a bit of the exception. It appears that the rail company is trying to push sales of season tickets. Too bad this chart doesn't bring the story to the front.
Here is one attempt using paired bar charts.