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Cool dynamic demographic maps provide beautiful illustration of Chris Rock effect

Robert Gonzalez reports on some beautiful graphs from John Nelson. Here’s Nelson:

 

An animated GIF dot density map of males and females throughout life, in New York City.
The sexes start out homogenous, go super segregated in the teen years, segregate for business in the twenty-somethings, and re-couple for co-habitation years.  Then the lights fade into faint pockets of pink.

 

I [Nelson] am using simple tract-level population/gender counts from the US Census Bureau. Because their tract boundaries extend into the water and vacant area, I used NYC’s Bytes of the Big Apple zoning shapes to clip the census tracts to residentially zoned areas -giving me a more realistic (and more recognizable) definition of populated areas. The census breaks out their population counts by gender for five-year age spans ranging from teeny tiny infants through esteemed 85+ year-olds.

And here’s Gonzalez:

Between ages 0 and 14, the entire map is more or less an evenly mixed purple landscape; newborns, children and adolescents, after all, can’t really choose where they live – let alone where they’re born. But between the ages of 15 and 19, something interesting happens. As Nelson writes on his blog:

We are in the age-span where teens/young adults can choose where to live. And they choose paths that are not gender-neutral. Immediately we see clusters of females and, to a lesser extent, clusters of males. What’s the deal? College. And prisons.

Morningside Heights positively glows pink as the home of Barnard College, as do other institutions of learning sprinkled throughout Manhattan. The garment district is another draw.

We also start to see the filling of Rikers Island with green dots as young men begin to populate the jail complex. . . .

The analysis for other age groups continues in greater detail over at Nelson’s blog. In their early twenties, for example, professional women tend to gather in Midtown Manhattan, while swaths of early-twenty-something masculinity emerge in places like the SUNY Maritime College, and Yeshiva University. . . . The forties and fifties are characterized by a re-segregation of genders, and a thinning population. . . .

[Nelson] continues:

At 85 and older, New York is essentially pink. Women outnumber the remaining men at a rate of better than two to one. Various retirement communities popular with women become apparent, almost as strongly as their geographic preferences in their teens and twenties. Those two eras mark their times without men, when whole neighborhoods are almost empty of males their peer. The boys have moved on.

Gonzalez concludes:

Who knew a map could be so poignant?

These maps are a beautiful illustration of the Chris Rock effect. Chris Rock says things we all know are true. But he says it so well that we get a shock of recognition, the joy of relearning what we already know, but hearing it in a new way that makes us think more deeply about all sorts of related topics.

In the past, I’ve used the Chris Rock concept to understand the different attitudes in statistical graphics and information visualization. Statisticians, following John Tukey and Bill Cleveland, emphasize the ability of graphical data displays to reveal things that we have never thought of before. In contrast, graphics designers celebrate innovative designs and visual juxtapositions that reveal interesting aspects of data but without highlighting any particular comparisons.

I’m happy to discuss the Chris Rock effect in the context of Nelson’s maps, because this should make it clear that the Chris Rock phenomenon is not a bad thing. It’s not a put-down of a graph to say that it reveals things we already know (and, for that matter, I’m a big fan of Chris Rock). Re-saying what we already know, quantifying it, and expressing it in other ways, is an important part of how we get to understand the world.

P.S. Nelson also writes:

I, along with most other cartographers these days, am really into dot density mapping. It is way more truthful a means of presenting relative geographic dispersion and affiliation than, say, choropleth mapping, which will be the carto-whipping-post of 2013.

I’m not all that into carto-whipping myself, but I agree with Nelson that dotmaps are cool, and I’m glad that technology has caught up with this excellent idea.

21 Comments

  1. Wonks Anonymous says:

    This may not be completely on topic, but you’ve often complained about economists focusing on “testing hypotheses” rather than doing descriptive statistics and just learning interesting stuff. After the recent EconNobel announcement I decided to check Dimensional’s Fama-French blog to see if it had much new content recently, and while it was dissapointingly sparse it did have an interesting bit where Fama linked to the best advice he’d ever gotten, from his statistics professor Harry Roberts:
    “With formal statistics, you say something — a hypothesis — and then you test it. Harry always said that your criterion should be not whether or not you can reject or accept the hypothesis, but what you can learn from the data. The best thing you can do is use the data to enhance your description of the world.”

    • Andrew says:

      Wonks:

      That’s a great quote. Except that I disagree with what Fama says about “formal statistics.” Or, should I say, he has an old-fashioned view of formal statistics. Nowadays, lots of formal statistics is all about what you can learn from the data, not just about testing hypotheses. And I’m not just talking about Bayes here. Think of all the non-Bayesian work on signal processing, lasso, etc. To put it another way, during the past 50 years, statistical theory has caught up with this aspect of statistical practice.

      • Wonks Anonymous says:

        Well, another of your gripes about non-statistician social scientists is that they use techniques that might seem impressively mathy but any of their colleagues in the stats department could have told them was inapt. So perhaps not surprising someone who got his econ phd in the 1960s still has an old fashioned view of “formal statistics”.

  2. Louis says:

    Cool graph by Nelson. However, I do find that the purple/green is not bright enough against the black background (or the background to dark)…

  3. Robert Grant says:

    It certainly is nicely executed. I wonder how hard it would be to turn it from an animated GIF (the dataviz equivalent of the flint hand axe) into a properly interactive, filter-able, click-able, zoom-able JavaScript visualization. Not hard, I guess, except for the huge number of dots to be redrawn with each interaction.
    The only thing that bugs me is that their interpretation strays towards story-telling over the lifecourse (“as young men begin to populate the jail”), while this is a snapshot of a recent timepoint. This is so common with animation because time is such a compelling element that it really throws us to have any other variable mapped to it.

  4. derek says:

    That’s a bit unfair to choropleth maps. It’s not their fault that they tend to be used as “this shade represents x”, when they ought to be “this shade represents x per square mile”. With the latter, you wouldn’t be able to tell the difference between a very fine-scaled choropleth and a very dense-mapped dot density map, except that the latter would need far greater technological resources to create.

    If the criticism is that choropleths typically *aren’t* very fine scaled, that’s invariably due to the absence of the data, not bad presentation of it. The makers just didn’t have the information to that precision at all, it’s not that they had it and threw it away.

    Every dot density map I’ve seen has actually been a cheat: they without exception have wimped out, for understandable privacy reasons, of plotting each person as a precisely-positioned dot. Instead, they’ve scattered a roughly appropriate number of dots about the general area. Sorry, that’s a choropleth map, just using stippling instead of shading.

    • John Nelson says:

      Derek (if this is Derek Watkins, I’m a big fan of yours),
      I don’t dislike choropleth maps, they are a great platform for showing rates. The downside is that they only show one rate at a time. These dot maps (because I use color to denote gender) show both relative gender proportion *and* geographic density. If I were to do it again I’d use slightly bigger dots, for what it’s worth, but I’m still happy with the dot mapping choice. Also, dot density maps have the capacity to be more emotionally resonant, as a dot representing a human is more relateable than a keyed hue representing a proportional range of the local gender.
      So I only mean to bash choropleths a little bit.
      Semi-relatedly, if this is Derek Watkins, I’m working on something fun related to your recent update on Bill Bunge’s population blob map, and I’ll reach out to tell you more about it.

      Cheers,
      John

  5. John Nelson says:

    I can say with a confidence interval of 98 that I do not [not] like this post.

    • Andrew says:

      John:

      I don’t know what that comment means, but thanks again for making the maps. They’re beautiful and tell a great story! (I’m also curious about your dark color choices, given the comments above.)

      • Jesse says:

        I do know other people with an unnatural affinity towards green & purple(or pink). Or just any really loud color combination clashes. I found an excellent example once where blue/yellow ended up looking much better, but don’t think colors used here clash quite as much(like nails on chalkboard) as my now slowly much despised purple/green.

        My current theory is that it’s an ingrained concept rooted in R or some other common default which makes it harder for people to objectively see how it looks purely from aesthetic pov. Which isn’t as bad as color confusing / hiding / overemphasizing one dimension of data and another unintentionally.. But these days the bar is quickly going up. Nytimes and similar people are exposing old accepted flaws.

        Of course my opinion is meaningless beyond color choices since I’m not remotely qualified to have a statistical opinion on overall weightier concepts..

      • John Nelson says:

        I thought I was making a cute statistical statement. Null hypothesis or something. Anyway, thanks for your coverage and insights.
        The gender colors I chose are, by way of hue families, so culturally ingrained I thought it best to leverage that collective information. I was careful to ensure that each color was equally “light” (in a black and white version they have equal brightness). I could have gone light or dark for the background and thought that the dark platform did the better job of illuminating the data. Though I do wish I’d made the people dots a bit bigger. There are always tweaks in hindsight. But overall I’m happy with the way that they illustrate an interesting phenomenon, which is a sort of portrait of our lives.

        • Steve Sailer says:

          Thanks for using pink for girls. That makes the graph easier to interpret.

          I notice that a lot of demographic graphs these days go out of their way to use non-stereotypical colors, such as blacks are yellow, whites are black, Asians are brown, Hispanics are white, and American Indians are green.

  6. Steve Sailer says:

    This graphic shows the remarkable number of young women in Manhattan these days. I’m from L.A., so I’m used to seeing a lot of attractive young women around, but recent trips to New York have been eye-opening. Manhattan on a Thursday evening looks like one giant set for a romantic comedy movie.

    A third of a century ago, when the Dow Jones Average was under 1,000, Manhattan lagged West L.A. in abundance of attractive women. But now, after 31 years of Wall Street being immensely profitable, New York is much richer and is therefore more attractive to young women.

  7. Kyle says:

    Dot maps are great when density is a relevant attribute, but if I want to compare rates/means I’d hate for Wyoming to disappear completely…

  8. Louis says:

    I have no quarrels with green/pink. To me it is just not that easy to follow because it all seems pretty dark. That was no stab at the designer but just some feedback.

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