An amazing amount of data is being visualized here. Mousing on the mapwill pick up the specific data for each county. There is a bar up top for discovering the evolution over time. It would be great if there is an animation button so the map can be played out without clicking. An animated gif will also do (similar to the disease map we featured some time ago).
The colors on the first map represent the origin of the top ethnic group in each county. Within each group, the tint of the color further displays the percentage of the population that group accounts for. The subgroups appear to be 0-2%, 2-5%, over 5%. The last subgroup is very wide.
Not so keen on the second map with all those bubbles. They show the number of people from each country by county. The bubble size is proportional to population. Every version of this map looks the same because the population is concentrated in the cities and the interior is sparsely populated, no matter what ethnic group.
Regardless, this is another laudable effort by the crew at theTimes.
Reference: "Immigration Explorer", New York Times, March 10 2009.
From Bernard L., another exemplary effort by the Times. This one really got me excited.
The set of line graphs shows how demographics of students in American schools have evolved in the last two decades. Here, I selected New York City schools, and the tool sensibly decided to compare those with New York State schools (gray line).
There is so much to learn from one simple chart:
The blue and gray lines are almost parallel everywhere, which tells us that in terms of the change in demographic composition, New York City pretty much resembled New York State during this entire period.
However, in terms of demographic composition, rather than the change in composition, New York City schools are very different from the rest of the state, in that the proportion of white is lower by a third while that of minorities are much higher, especially black and Hispanic students.
State-wide (as well as city-wide), black and white students have been declining as a proportion while Hispanics and Asians have increased.
The extent of the change is immediately visible, Asians have jumped from 7% to 14% for example.
From a graph design perspective, the execution is very clean. Data labels are limited to the first and last values. A small multiples concept is used with the ethnic groups placed side by side. A great awareness of foreground and background as well. And imagine how much data has been visualized here, and be impressed. You can look at any county in the country.
Here's one where the county change does not exactly mirror the state change (Napa in California):
Reference: "Diversity in the classroom", New York Times, March 12 2009.
The chart on the right which compares the unemployment picture across past recessions has many good features.
It uses a very sensible metric, counting the percentage change from peak employment. I have mentioned the superiority of this type of presentation compared to plotting a time series of unemployment rates. The following is an example of a standard graphic using gray bands to indicate recessions. The difference is obvious.
Here is the previous post that dealt with the drop in market capitalization of banks since the peak which screamed out for this type of treatment.
It handles the foreground-background issue very well. A number of similar charts is circulating in which every single line has a different color. Here, the designer clearly tells us the current recession is the foreground and all the past recessions form the background. It looks as if the 1981-3 recession is slightly highlighted with a darker orange to draw attention to the fact that it is most similar to the current situation. I find this unnecessary because the association is clear even without the darker hue; however, the designer does this with a very light touch so this is just a question of taste.
The original graph threw us off our sense of scale. It seemed to be saying all these oil companies are roughly the same size but one grew much faster than the others. The red color and the setting off of the data above the title of the chart seemed to announce some important find.
The junkart version on the right reversed everything to our normal sense of scale. It is a version of the bumps chart, one of my favorites.
So we find that Total is the smallest of these oil companies, about half the size of ExxonMobil -- you wouldn't know that from those abysmal bubbles! Adding to the problem is that the growth data is used to sort the companies while the actual production data is hidden in the data labels.
Total is indeed growing faster but BP is not far behind. The fall of ExxonMobil and Royal Dutch Shell is equally intriguing.
Chris P pointed us to the "Financial Comeback" calculator, surely a well-meaning joke from the folks at the Times.Here is how one gets to make a 40% loss back in just six years!
Surely, someone has to tell them about simulation. They have to assume a probability distribution on the annual returns, and show us some sample paths. Using the average annualized historical return in essence wipes out all variability and no wonder it's smooth sailing upwards. Eternal optimist.
Here is Chris' comment:
The bad news is that the range of values it offers does not include the return on the market from last year (-31% to -36%). I guess they are optimistic.
The interactive features of this chart, however, impressed me. The smooth adjustment to the chart as one slides the control, including the automatic choice of appropriate axis labels, is very nice indeed.
Okay, they want to trademark the name of the calculator so perhaps this is serious.
Reference: "Calculate your financial comeback", Jan 6 2009.
Right on the heels of the disastrous bubble chart comes another, courtesy of the NYT Magazine. Bubble charts are okay for the conceptual ("this is really big, and that is really tiny"). This chart wants readers to compare the sizes of the bubbles, which highlights the worst part of such graphs.
Poor scaling is the huge issue with bubble charts. They are the prototype of what I call not "self-sufficient" charts. Without printing all the data, the chart is unscaled, and thus useless (see below middle). When all the data is printed (as in the original, below left), it is no better than a data table.
In the above right chart, we simulated the situation of a bar or column chart, i.e. we provide a scale. For this chart, the convenient "tick marks" are at 10, 20, 34, 41. Unfortunately, this scaled version also fails to amuse.
Note further that the data should have been presented in two sections: the party affiliation analysis and the gender analysis. Also, it is customary to place "Independents" between "Republicans" and "Democrats" because they are middle-of-the-road.
A profile chart is an attractive way to show this data. Here, we quickly learn a couple of things obscured in the bubble chart.
On the issue of abortion, Independents are much closer to Democrats than Republicans. Also, there is barely any difference between the genders, the only difference being the strength of support among those who want to legalize.
Reference: "A matter of Choice", New York Times Magazine, Oct 19 2008.
PS. Based on RichmondTom's suggestion, here are the cumulative profile charts.