Tuesday is Election Day in the
United States. If history is any guide, we can expect to see a whole lot
of maps on Wednesday that look something like what’s displayed on the
left-hand side of Figure 1. But it’s important to keep in mind that we
live in a country that looks a lot more like the map on the right-hand
side. In this post, we’re going to talk about some of the problems with
the map on the left and how we can move to widespread use of something
more like what is on the right.
Before we dive in, it is important to note that in the maps that follow, red means Republican and blue means Democrat.
The map shown on the left in Figure 1 and in greater detail in
Figure 2—technically referred to as a choropleth map—is great if all you
want is to quickly convey how a state’s Electoral College votes were
assigned. They are awful, however, for conveying how the U.S. population
actually voted. Anyone unfamiliar with the outcome of the 2012 election
could be forgiven if the casual viewer came away with the impression
that Mitt Romney won that election. After all, something approaching 63
percent of the map is red, but Barack Obama actually won 51 percent of
the popular vote and 62 percent of the Electoral College. Yet, because
(most) states’ electoral votes are assigned “winner take all” and
because states vary in geographic size and population, these maps
actively mislead viewers to think that more of the country voted
Republican. Take Montana, for example. It has only one-third of the
electoral votes of Maryland but represents 12 times as much space on the
This problem could be corrected by using a stylized map that makes
each state the same size (such as the one in Figure 3, based on a
frequently used National Public Radio
design). But while this corrects
for the geographic size differences between states, it’s not a huge
improvement over the original map. The map below still leaves viewers
with the incorrect impression that our nation is cleanly divided by
political affiliation. That is simply not an accurate image of the
United States. And we can prove it with better maps.
Instead of focusing on electoral votes, let’s instead focus on how
people actually vote. With that goal, we can do a lot better than the
above maps by altering three elements: color, geographic aggregation,
Virtually every election map shows Republican-voting states as red
and Democratic-voting states as blue. This is fine, if everyone in each
state voted for the same candidate. But, of course, that is never the
case. In 2012, only the District of Columbia had more than 90 percent of
the population voting for one candidate. Every other state had 75
percent or less of the population voting for the winning candidate. Most
states, in fact, had between 50 percent and 60 percent of their
population voting for the winning candidate. None of that
differentiation is captured in typical electoral maps.
The most obvious way to fix that is to alter the shading to reflect
the proportion of each state voting for a candidate. The map below
keeps the same shade of red to indicate 100 percent of votes were cast
for the Republican candidate and the same shade of blue to indicate 100
percent of votes cast for the Democratic candidate. But it adds a third
color—purple—to represent where an even 50 percent of voters selected
each candidate, and then uses a gradient of purple to represent any
percentages above 50 percent—adding more red or blue as appropriate.
Contrast this result (Figure 4) to the electoral map (Figure 2). It’s
the same map, produced with the same data and program—just with
The message conveyed by Figures 2 and 4 couldn’t be more different.
Figures 2 and 3 suggest a deeply divided country with huge swaths of
the country either entirely Republican or entirely Democrat. Figure 4
suggests something very different: a country where party state in every
state is nearly identical. While some states may lean slightly toward
the red (Utah) or the blue (California), the overall message of the map
is that all states are some shade of purple.
Should the goal be to illustrate voting patterns instead of
Electoral College patterns, then the maps must be based on something
other than states. States are, of course, very big—causing a significant
amount of variation to be hidden away. Is northern Illinois (which
includes the city of Chicago) really the same as southern Illinois? How
about upstate New York versus the New York City region?
So another improvement to make is to reduce the level of geographic
aggregation. Ideally, the map would use the smallest level of
aggregation possible: the voting precinct. Unfortunately, while these
data are available, it’s actually hard to obtain, aggregate, and map.
Instead, the maps below use the smallest level of geographic precision
that is easily obtained: county level data.
Figures 5 and 6 map counties rather than states. Figure 5 shows two
colors (as in Figure 2). Figure 6 shows a continuous scale (analogous
to Figure 4).
Here again we see that the country is not blue or red, though more
gradations now appear. Unlike Figure 5, we can now see areas that are
clearly more red or blue than purple. We can also begin to see blue
clusters in traditionally red states (Texas) and vice versa
last oversimplification in the traditional electoral maps is that they
fail to account for the uneven distribution of the U.S. population.
Simply put, huge swaths of the United States just don’t have many (or
any) people living in them. More than 50 percent of the U.S. population
lives in states along the two coasts. And just 25 percent of U.S.
counties hold 90 percent of the population. Mapping at the state or
county level thus gives disproportionate weight to sections of the
country where there are not a lot of people.
One approach that others have taken to correcting for this is to
create a cartogram. A cartogram scales each geographic area to a size
proportional to some other variable (for example, population size). In
the process, it attempts to maintain the general shape of the map, but
distortions are inevitable (see, for example, this approach
But if a more realistic representation of the United States is
desired, another approach is needed. One alternative would be to
manipulate the opacity. That is, a map could maintain the same shading
but reduce the transparency of counties with low populations.
Unfortunately, in trials of this approach (not shown), the resulting
maps are difficult to read.
Instead the map below uses alternative approach. Figure 7 maintains
the same shading shown in Figure 6 but removes all census blocks that
have zero population (that is, all areas where no people live are
colored a neutral white). While this doesn’t completely correct for
population discrepancies (after all, an area with one person is
displayed with the same vibrancy as an area with 10,000 people), it does
correct some of the significant misrepresentations of Figure 6, where
largely uninhabited areas (such as large portions of Utah) are shown as
If all you want to know is which direction a state’s electoral votes were assigned, the typical election night map is all you need. But if you really want to study geographic patterns of voting, a more accurate and nuanced map can be developed and presented. What do you think is the most effective way to represent the voting patterns in the upcoming presidential election?
About the Data and Maps
State election data is from the Federal Election Commission and can be found here
. County data is adapted from data stored here
. All maps were created using the R programming language using geographic data from the U.S. Census Bureau