Visualizing WPA expenditures

why not just a log scale?

it “smells” like a power law, but how does that involve the categories? Is there some organizational principle at work here? Assuming categories track management structure and that each manager has some reasonable number of direct reports, then at each level there can be a few direct reports managing “big” projects in a “fixed” category (e.g. roads) or closely related areas and some general purpose managers managing “mixed” categories. It would be amusing to work out the model and see if you could predict the organizational parameters (# of direct reports, fraction of fixed/mixed), and compare that to the actual structure.

note I’m way out of my zone on the historical/economic particulars here, so all this may be total crap or completely obvious to the casual observer. :)

Why should there be “rules” for visualization of data? As with any other form of communication, the most appropriate form of data presentation depends on the audience to which it is addressed and the context of the communication, so the whole idea of there being generic (non-audience-specific) rules makes no sense.

Peter’s broken link should I think go here.
BTW, is there a word for an empty Wikipedia page? A wik’ole? (I looked up “nothing” in this online Hawaiian dictionary.)

Kieran:

“Because there are more and less effective ways of presenting data.”

Sigh. This statement only has meaning given an intended audience and given a context for the intended communication event. Effective for whom? Effective for what purpose?

Has the last two centuries of writing on the philosophy and sociology of language been in vain, I wonder.

Suggestion – could you use a different colour background for each of the progressively bigger sub-scales, so as to make it visually intuitive that something is changing between each one? Or perhaps make the backgrounds of each one cover different areas?

The one problem I see is that the labels at the top can create confusion regarding the labels at the bottom. When I first glanced at the right-hand panel, I briefly thought that it was saying that the WPA had spent $5,000 BILLION dollars on roads, not $5,000 million, because I wanted to apply the label at the top to the label on the bottom. The correct unit label is two panels away to the left, while the upper label saying “Billions” is right there.

The basic idea isn’t that bad, but I think you’d be better off doing the bottom labels differently– changing the rightmost panel to $1 Billion, $2 Billion, etc.

As noted above, of course, this depends a great deal on the intended audience.

I’ve nothing but admiration for your graph. Perhaps that is because I struggled with the two previous iterations and thus find myself as the perfect intended audience. Thanks, good work.

I would add that the discussion of the New Deal over at Edge of… is very informative; we’re seeing another outbreak of the old ‘the New Deal prolonged the Great Depression’ lie, so it’s good to have a source of actual information.

Maybe you want facet_grid(…, shape = “free”)? I’m guessing you’re using a custom breaks and labels argument for the x axis, rather than modifying it afterwards. (It looks like you missed 70)

p.s. it’s really nice to see ggplot2 in the “wild” :)

“sewing”?

My irritation is with people who consider there to be such things as generic rules for communicative acts without regard to audience or context, despite all the evidence against such such things.

Says the person who is writing in grammatically appropriate sentences, which obey generic rules for the communicative act of writing. Or in a different context, would you have said rriiion aymt pswiht audnlascoa and expected to have gotten your point across all the more efficiently? Being a human being, communicating to other human beings who share a common language, implies enough context to start making at least rudimentary judgments about efficiency.

That having been said, the panel discontinuity of this graph is an excellent tweak. What a log scale tends to mask, this clarifies pretty well. I still get the immediate impression of what spending dwarfs what other spending, and I can compare two values relatively easily.

that means that a first glance shows an almost flat rise when, in fact, there are different scales involved

…in general, for this kind of data, we’re not trying to determine whether there’s a linear or cubic or what-have-you relationship between points. We’re comparing quantities that in some sense are not determined by one another. People who aren’t scientists and don’t work frequently with models themselves won’t make the immediate association between an approximate-linear graph and the rather sophisticated notion of slope. You look at this graph and you see roads all by itself, in a block set aside all for itself: you get the idea that spending on roads dwarfs nearly everything else. It’s not as skull-crushingly obvious “at first glance” as a basic log scale, but Kieran’s striking a balance.

It’s striking how complex even quite simple data can be to present effectively.

I’d have preferred: 1, more room between each continuous block. 2, that billions be expressed as thousands of millions along the horizontal axis (the use of 1bn, 2bn, etc was a little ill-advised). Other than those minor aesthetic tweaks, this presentation seems very effective.

Apologies for the double-post, I thought a bit more about it… The thing is, I am wondering whether a simple table with numbers would not be more effective than this particular graph. The advantages of a graph over table would be that you can visually compare magnitudes, and that patterns such as breaks are clearly visible.

But this particular graph makes visual comparison impossible without looking up the actual numbers on the scale, and the breaks and their relative importance are only noticable if you study the graph really well. If you just printed the numbers, the larger number of digits would show the breaks at least as clear as this graph.

Or to put it a little more shaprly — by arbitrarily adjsuting the horizontal scale, you can give a curve like this whatever shape uyou want. But what does a graph tell you about the underlying data when its shape is simply imposed by hand?

“why not just a log scale?”

That’s almost what it is. In the original discussion people were looking for a stronger way to remind the viewer about the scale changes in such a case.

I would say you’ve made a weaker way. It’s not at all obvious that the scale is discontinuous visually — you have to read the fine print.

If you are going to graph it this way, I greatly prefer larger breaks between the categories plotted on different scales, both horizontally and vertically, also different colors used for the dot plots at different scales would also serve to alert the viewer that something is going on. It’s extremely difficult to visualize from your graph, the difference at the boundary of the scales.

There appears to be a bigger difference between recreation and airports/airways, than between conservation and sewing, where the plots are right next to each other.

That would be somewhat alleviated by more obvious visual breaks, but a simple log scale would avoid the problem completely while conveying at least as much visual information as this graph.

I prefer the log scale. or, as your last comment suggests, a table with full dollar amounts (or amounts in thousands/millions) which would make the arithmetical differences clearer without losing information.