But Charlie, damn fine post on the subject, seriously -I enjoyed the formatting and style as much as the content.
The first set of bullets following the taxes graph clearly outlines what this type of graph excels at. I don't think those reasons overlap very neatly with sparklines; which are better at showing trends in time series data in a very small space. To me the key point about these slope graphs is that they show the relative rates between subjects very clearly. Sparklines do not do that as well, indeed they are often pretty compressed along the y-axis.
Then you get nicely antialiased graphics.
Don't go crazy on the expansion though or iPhone users will hate you.
You should also be careful to drop your endpoints of horizontal and vertical lines on the xxxx.5 boundaries (in screen space) to keep nice sharp lines, otherwise you get a two pixel wide smear.
I might pick my Canvas experiments back up, then, as R and the other packages are outside the scope of my day-to-day work, but I could see a JS implementation being useful. Thanks again.
I'll +1 the recommendation though. D3 is (unsurprisingly, coming from Mike Bostock: http://bost.ocks.org/mike/) brilliant.
By selecting the two scales used, the designer of the graph -- whether intentionally or not -- is introducing meaning where there might not actually be any.
For example, should the right-side data points have been spread out so that the highest and lowest points were as high and low as the Switzerland and Mexico labels (the highest and lowest figures, apart from the US) on the left? Should the scale been adjusted so that the Switzerland and/or Mexico lines ran horizontally? Each of those options would have affected the layout of the chart. I’m not saying that Uberti should have done that -- just that a designer needs to tread very carefully when using two different scales on the same axis.
For anyone else that enjoyed this and is not aware of Parallel Sets: http://eagereyes.org/parallel-sets
Personally, I've found few good real-world use cases for PSets. But I've found it to be helpful for experimenting, even though I rarely use it for any end-product charts.
[edit: One last thing before I'm out of range. I'm sure most folks interested in this are familiar, but if not... BumpCharts: http://junkcharts.typepad.com/junk_charts/2005/07/in_praise_... ]
> Another difference I should note: This type of forced-rank chart
> doesn’t have any obvious allowance for ties. [...] In Fry’s case,
> he uses the team with the lower salary as the “winner” of the tie.
> But this isn’t obvious to the reader.
Really? I've definitely read about sparklines, but I've never seen one used naturally, as it were.
(Google analytics product pages seem to be down for me)
I don't have examples off-hand, so I hoped I've explained what I mean well enough.
The names of the countries are printed twice. As far as data is concerned, one set contains none. The second printing may help readability, but readability isn't data.
You can tell one set isn't necessary because the cancer graph at the bottom leaves them out of the middle columns.
The bullet point at the bottom "Include both the names of the items and their values on both the left-hand and right-hand axes" could add "If your goal is zero non-data ink or your space is tight, you can leave out one set of names."