Unemployment Map FAQs
- What is this a map of?
- This is a map of seasonally adjusted unemployment by county by month
in the United States. You can view it either as a population-based
cartogram or in an ordinary Mercator projection.
- What does "seasonally adjusted" mean? Why do you need to adjust?
- Many places have seasonal ups and downs. For example, there are
not many agricultural jobs in Minnesota in the winter. Counties
with large universities tend to have fewer jobs during the summer.
If you do seasonal adjustments, it is easier to see when a change
in unemployment is something to pay attention to and when it is
normal and expected.
- How did you do the seasonal adjustment? Why didn't you just
get those numbers from the Bureau of Labor Statistics?
- The Census Bureau does not provide seasonally adjusted numbers
at the county level, only at the national level. They use a
complex program called
to do seasonal adjustments. ARIMA has several parameters, and
it looks to me like the parameters would be different (and
require hand-tweaking) for each of the approximately 3100 counties.
Instead, I used a function built in to the
R statistical package
to smooth the
unadjusted by-county data
that I got from the Bureau of Labor Statistics.
- Why is the map all distorted?
- It is a population-based
meaning that the areas are distorted so that the area of each
county is proportional to the county's population.
- Why does the Continental US cartogram look so much bigger compared to
the standard (mercator) projection?
- Because it sucked up a lot of the pixels from Alaska. Alaska has
a huge land area, which looks even bigger than it really is because
of the distortions from a Mercator projection. Meanwhile, Alaska
has a very low population compared to the Continental US, so the
Continental US essentially "sucked up" all the area from Alaska.
- Why didn't you just cut out Alaska then? Wouldn't that make it
- I did try it without Alaska, but that took a fair bit of extra work,
didn't change the shape of the Continental US states (just the
size), and Alaska is a legitimate member of the United States. Alaskans
have unemployment, too!
- Why do all the states look "fat"?
- They don't. Populous states -- which tend to be on the oceans
and so perhaps the ones you see first -- end up kind of fat-looking
because they suck up area from other states. However, states with
a low population end up looking scrawny. Not just Alaska, but the
northern mountain states (e.g. Wyoming and Montana) look sucked-in.
- Why do the city names appear and disappear as you move the map around?
- People did not build cities in locations which were convenient for
map makers. Dallas and Fort Worth, for example, are so close
together that showing both on a map (especially a non-cartographic
map) would be ugly and/or confusing. The Big Map Players probably
make lists of which cities to show at every zoom level. I'm sorry,
but I don't have the budget to do that.
Instead, I go through the cities in order of population. If I
come to a city which is too close to a city which has already has
its name on the map, I don't show that city's name. When I get
to 25 cities on the viewable map, I stop.
This means that if you move a city so that it is no longer visible,
that might "unblock" a smaller city. For example, if you move
the map to the right until New York isn't visible, Newark will probably
appear (at the default zoom level).
- Why don't all of the county borders get drawn sometimes?
- If the counties are too small, then the borders take up so much
of the room that it's hard to see the unemployment colour.
- Why did you just say "colour" there?
- I am a US citizen, but I live in Canada now.
- What controls aren't obvious?
- If you click on the county graph, the map will change to show
the country's unemployment as of the date you clicked on.
- What is interesting about these maps?
- The cartograms are interesting for showing just how many people live
in cities compared to the country.
What I found more striking about the unemployment data was:
- The crash of 2008 was very bad. The difference between July
of 2008 and November of 2009 is stark.
- Hurricane Katrina was very bad. If you look at the period
between September 2005 and June 2006, you will see that
the area around New Orleans is grey. That means they couldn't
even collect data. This is the only time and place since
January 1990 where they couldn't collect data. (Hurricane
Sandy, by comparison, doesn't have much of an effect on the
maps.) Counties in the vicinity of New Orleans which did have
data had extremely high spikes in unemployment.
- It sucks to be Detroit. (There are other counties which also
have chronic unemployment, like Imperial County CA and Yuma
County AZ, but they aren't nearly as populous.)
- Populous counties tend to have smaller seasonal variations
than smaller counties.
- Why do the Katrina-ravaged Louisiana counties show some non-zero
unemployment value if no data was collected?
- Because of how R works, the seasonal adjustment was applied to all
months, not just the months which had data. (If you look carefully
at the pale blue line, you'll see that it actually is flat at
zero during that period.
- Can you see the effects of other hurricanes on unemployment?
- Nothing as dramatic. There seem to be small decreases in
unemployment in Florida right after Hurricane Andrew (Aug 1992) and
in New York after Sandy
(Oct 2012), but the decreases are minor. For your reference, here are
the dates of some destructive hurricanes:
- Andrew Aug 1992
- Charley Aug 2004
- Ivan Sept 2004
- Wilma Oct 2005
- Ike Sept 2008
- Irene Aug 2011
- Sandy Oct 2012
- How did you make the cartograms?
- I used the program
implements of the Gastner/Newman  cartogram technique.
(Newman has another implementation on his web site.) I defined cartogram parameters manually,
and used 6000 points for the first grid, 1024 for the second, and
3 iterations. As a starting point, I used the
from the US Census Bureau. For the population, I used the Census Bureau
- Are the population estimates you used to make the cartograms accurate?
- Not very, unfortunately. The intercensual estimates are just an
interpolation between the two every-ten-years census figures on
either side. They are okay for a rough estimate, but they won't
show dramatic changes (like the post-Katrina exodus from Louisiana)
- How do you make the map tiles?
- I use a framework that I wrote myself in PHP. You can read
more about the technical details in a blog post,
Optimizing Map Tile Generation.
For this map, I actually pre-rendered complete (static) tiles
for zoom levels 0-5, just because there are so many and you can
whip through them so quickly by clicking on the county graph or
by hammering on the "Next Month" or "Previous Month" buttons.
Tiles at higher zoom levels have the geometric skeletons pre-rendered,
but the colouring is done on-the-fly.
- Why does the name Newman sound vaguely familiar in the context of cartograms?
- Probably because he did the Purple America elections cartograms.
- How did you make the graphs of the unemployment by county over time?
- Using the
R statistical package.
It has really great graphing tools.