Immigration to the US | Absolute Numbers
Immigration to the US | Absolute Numbers, courtesy of Thomas Brown and IBM's Many Eyes Tool


Immigration to the US 1900 - 2000 | Relative flows from sending countries
Immigration to the US 1900 - 2000 | Relative flows from sending countries, courtesy of Thomas Brown and IBM's Many Eyes Tool

What Works

Before you read any further, ask yourself which one of these graphs is most useful. Which one has the most information? If you had to get rid of one of them but still be able to explain the basic flows of people into the US over the last century, which one would you keep? And would your story be much weaker, somewhat weaker, pretty much the same after the loss of one of the graphs?

First, I was moaning the other day about a graphic – like the one I posted recently about prescriptions for treating mental illness in the US – in which color is used to make it look like there is important information being encoded when, in fact, the colors are just pretty, nothing more. I am happy to report that in this case, the colors are not only useful, but necessary. Try to imagine looking at this thing in gray scale. It would be nearly impossible to read. So kudos for color in general. In specific, I probably would have tried to group the countries that are near each other in the world within a color family. Sweden and Norway are good examples of what I would have done throughout – they are both green, just different shades. That makes good logical sense. On the other hand, Ireland and the UK are not in the same color family and it confuses me. I also don’t see great geographic or other similarities between Canada/Mexico and China. So I would have kept the Canada and Mexico as they are and found a different color for China.

Now I’m going to get back to the question I asked at the beginning of the post: could you do without one of these graphics if you had to axe one? It’s a leading question and the answer is clearly: yes. The first one is far better than the second one. Looking at absolute flows by country of origin gives a much more interesting and fully articulated picture than looking at the relative values of people coming at any one point in time.

What Needs Work

The numbers behind this graph were pulled from Census Data, a good place to go because they are the most reliable numbers we are likely to find (at least with respect to legal immigration – undocumented immigration is, well, undocumented so the Census doesn’t help). However, the thing about Census Data is that it’s going to show us flows for a decade at a time and I wonder if it might be a little misleading to show these numbers as an augmented line graph. A bar graph might be better and here’s why: smoothing the lines implies decade reliant time trends that don’t exist. Unfortunately, in the real world, important decisions do not always take place in the same year the census is taken. The Immigration Reform Act of 1965 was right between decades. Now I know you’re thinking something along the lines, ‘anyone who studies immigration is going to know when that reform act was and when WWI, WWII, the Depression, and all sorts of other important historical events took place. we’re not idiots.’. I agree; you are not idiots.

On the other hand, if I were to create this as a bar graph, I would have the freedom to actually locate the legislation as a graphic element – a line flying a flag announcing the name of the act, for instance – right between the bars for 1960 and 1970. But of course, that would make it difficult to see how the flows are changing over time, so I might superimpose a kind of shadow version of the current line graph over (or under) the bars so that the eye can be aided in its path from one bar to the next. Line graphs do show change much better. But I like the idea of being explicit with the time periods in which the measurements occur and with the notion of leaving graphical space to add important contextual details.

This graphic was created by Thomas Brown using IBM’s free Many Eyes visualization tool. I wholeheartedly support IBM and the other companies and organizations that are making powerful visualization tools available for free. In case you aren’t familiar with them, they allow users to input data and then they take that data and produce visual representations of it. In this case, the full version of the graph is interactive – hovering the mouse will reveal greater detail about any given flow at a point in time. This is a great thing. I support layering of information. The layering available at Many Eyes does not quite make up for the inability to layer in the way that I described above, but I’m not disappointed with IBM. There are already tools for manipulating graphics. The best way to use IBM’s tool is not to expect it to do everything, but to take their visualizations and then further enhance them in photoshop or your favorite image editing software.

Also Note

This graphic is about spaces but it is not a map. For whatever reason, people use maps whenever there is mention of geography, and even sometimes when there isn’t, even though the map is often not adding to the story and making it harder to immediately grok what the important patterns are. Just because geography or mobility might be part of the story you are trying to tell, it isn’t necessary to use a map to encode your narrative visually.


Thomas F. Brown. Immigrant Origins via email on 11 October 2010.

IBM’s Many Eyes data visualization tool.

US Census Historical Statistics for Immigration by Number and Rate and Immigration by Leading Country or Region of Last Residence.