Virginia Votes 2013

Tuesday is Election Day, and in Virginia the races for governor and other state executives are making plenty of headlines. But in addition to these high-profile offices, Virginians will also be choosing new representatives for the state's House of Delegates.

Actually, that's not entirely accurate. Many of the delegates who are elected won't be new. And in close to half of the house races, voter's won't have much of a choice.

Eighty-seven of the 100 house races feature incumbent candidates, 42 of whom are running unopposed. Of all the races, 45 have only one candidate on the ballot.

Virginia House of Delegates 2013
Candidate Parties in District Races
* = Incumbent candidate

In 2010, Virginia redrew district lines for the House of Delegates. Like the congressional redistricting process at the national level, Virginia's redistricting was based on Census results and intended to divide the state into districts of roughly equal population.

How did redistricting affect the competitiveness of Delegates races?

View larger

In 2009, before redistricting, 54 of 100 races included candidates from both major parties, and nine of those also featured at least one third-party candidate. In 30 races, major party candidates ran unopposed.

In 2011, the first House of Delegates election after redistricting, the number of races with candidates from both major parties fell to 27 — half of what it was two years before. Forty-three races saw Republican candidates running unopposed, up from 21 in 2009. Democratic candidates ran unopposed in 20 races, up from nine in 2009.

This year's elections will be more competitive, on the whole, than in 2011, but there are still more one-sided races than before redistricting. Forty-three races have both Republican and Democratic candidates, and seven of those also include third-party candidates. Republicans are running unopposed in 29 races, and Democrats are unopposed in 16.

The 2010 redistricting process also redrew lines for the state Senate districts. State senate elections won't be held again until 2015, but so far redistricting has offered mixed results in terms of competitiveness in the Virginia Senate.

View larger

In the 40 senate districts, the number of races with candidates from both major parties increased from 16 in 2007 to 24 in 2011. At the same time, the number of unopposed Democratic candidates fell from nine to three, while the number of unopposed Republicans increased from eight to 11.

The Virginia Public Access Project has some great information on the 2010 redistricting process, including maps and lists of precincts that changed districts between the 2009 and 2011 elections.

Data Sources: Virginia State Board of Elections, Election Results

Chart Tools: Google, Adobe Illustrator

Assignment 3: My Neighborhood(s)

Note: This post is inspired by an assignment from Dr. Brett Shelton's Data Visualization Theory & Practice course at Utah State University.

I recently spent a few days in my hometown of Durham, N.C., and it seemed like a great time to try to visualize the demographics of my hometown and my current home in Northern Virginia.

I'm using estimates from the U.S. Census Bureau's American Community Survey for 2011 — the most recent data available for most of these measures.

View larger

Based on my experience in both places, I expected to find significantly more people and more money in Fairfax County than in Durham County. The Census data confirms this, although I was surprised by the magnitude of some of the differences — and some of the similarities.

First off, more than one of every 300 people in the United States lives in Fairfax County. Hence the traffic at rush hour (and most hours, to be honest).

Taken as a whole the residents of Fairfax County are a little older than in Durham County, with a few more years of education and a higher rate of marriage. The different racial profiles are also interesting. On the whole I kind of expected to see greater differences in the demographics of these counties, particularly given the information in the next few charts.

View larger

On average, Fairfax County households have more than twice the income of Durham County households. The poverty rates are also startling. I suppose I should expect nothing else from the nation's fourth richest county. But why the difference?

Again, Fairfax County residents are a little older — perhaps farther along in their careers — and have a little more education. We can also see a slightly higher employment rate in Fairfax County (again, this is 2011 data) and, due to the higher marriage rate, perhaps a slightly higher rate of two-income households.

But more than that, I suspect the type of work being done in both counties plays a role in the income disparity. Take a look at the industries where people work in both places. The trade and service sectors are pretty comparable, but the largest industry for Fairfax County residents includes professional and management jobs. In contrast, the largest industry for Durham County workers is education, health care and social programs.

Also, it costs a lot more to live in Fairfax County. Housing is a big part of that.

View larger

As my parents remind me when I point out that a one-bedroom condo in Fairfax County costs as much as a two-story house in Durham, it's all about location, location, location.

I would love for one of the 2.5 percent of Fairfax County renters to let me in on the secret of renting property without paying rent.

Data Source: U.S. Census Bureau American Community Survey data for Fairfax County, Va., and Durham County, N.C.

Chart Tool: Adobe Illustrator

Bookstore Browsing

Recently I visited a large retail bookstore near my home and was struck by some of the oddly specific category labels above the bookcases. No need to go digging around a massive Computer section for a book on Photoshop — you can go straight to Digital Photography. Looking for the latest young adult vampire novel? There's a Teen Paranormal Romance section for that.

The bookstore employees must have thought I was strange or terribly indecisive as I wandered through the whole store with my iPhone taking note of the various genres and the number of bookcases devoted to each. I was curious — in a time when we get so much of our entertainment and information digitally, what do we buy in bookstores?

At first glance it looks like children's books, various fiction genres and cookbooks. But the real answer probably doesn't appear on this chart. If you've visited a chain retail bookstore lately, you know a significant amount of floorspace is devoted to CDs, movies, e-readers, board games, toys, gifts — things that aren't books at all. I've left most of those items out of the chart simply because the various racks, tables and shelves used to display them are difficult to compare to the standard bookcases. The massive "Bargain" section, which certainly includes some non-book items, is shown here.

I've used data from a bookstore in Fairfax, Va., a suburb of Washington, D.C., where the demographics include a lot of affluent, educated and professional families with children. I'm curious to see how the inventories of bookstores in other parts of the country stack up.

My first attempt with this data was a bar chart:

View larger

I spent a few days on this bar chart — one day on the admittedly unnecessary bookcase icon and the rest adjusting the bar size and trying to shoehorn in the category labels in a semi-legible manner. Success was mixed. My lesson here is that if one approach doesn't seem to be working, it's probably not the right approach. After about 30 minutes of reformatting my data spreadsheet to Google's liking, Google created the "tree map" at the top of the page in a few moments.

Data Source: Observations at Barnes and Noble, Fairfax, Va.

Chart Tools: Google, Adobe Illustrator

Extra Credit: More Freedom!

Is there a relationship between wealth and freedom? What about government stability? The Bubble Chart of Freedom is here to find out.

Again, I'm using Freedom House's Freedom in the World index. Today's chart focuses on the top 50 largest countries by population, and the freedom ratings are from Freedom House's scores for 2012.

There's a significant amount of research suggesting a strong correlation between national wealth and democracy. Perhaps I'll post a bibliography on the topic sometime soon. In the meantime, the data here seem to support that correlation. The Free countries in the green shades are mostly floating at the top of the chart, where the values for GDP per capita are highest. Not all Free countries are among the wealthiest — India and Indonesia are pretty low on the GDP scale — but almost all the wealthiest countries are Free.

The x axis shows how long each country's constitution (or in the absence of a constitution, the legal document establishing the current form of government) has been in place. The question I wanted to answer here is whether countries with more stable governments are more likely to be Free, with constitution age acting as a proxy for regime stability. It's a tricky measure, since it really doesn't say anything about the content of the constitution or how the government applies it, but hopefully it does help separate countries in transition from more established governments.

Because so many countries have been through significant transitions and adopted new constitutions within the last 50 years, the x axis scale is logged to alleviate some of the crowding between the 10 and 50 year marks.

The relationship between constitution age and freedom is not as clear as the one between wealth and freedom. It is interesting to note that none of the countries that adopted new constitutions in the last 15 years is Free.

Again, only the 50 most populous countries are shown here. The full data set might show a different picture — perhaps on a future post.

Here's the data in table form. Countries with Freedom House scores of 1 to 2.5 are Free, 3 to 5 are Partly Free, and 5.5 to 7 are Not Free.



Data Sources: Freedom House Freedom in the World reports.
Population, GDP per capita and constitution data from the CIA World Factbook 2013.

Chart Tool: Google

Assignment 2: Substance over Methodology — Freedom in the World

"Graphical displays should … induce the viewer to think about substance rather than about methodology, graphic design, the technology of graphic production, or something else"
— Edward Tufte, The Visual Display of Quantitative Information

View larger

I'm using one of my favorite data sets today to explore a particular challenge: How do you clearly illustrate meaning in data that don't have intrinsic meaning? Put another way, how do you explain the methodology behind data without distracting from what the data have to say?

The data in this case come from an index — Freedom House's annual Freedom in the World index, which scores every country in the world based on civil liberties and political rights. It's a very popular and useful tool for foreign policy writers and researchers who want to compare different governments to each other or look at governance trends over time.

Like any scoring system, though, it uses a manufactured scale to rank qualities that are not easily quantifiable. In order to understand what the scores say about freedom, first you have to understand how the scores are created.

I've seen (and tried) several different approaches to graphing Freedom House scores, and every approach has pros and cons. Trend lines are most common for charting scores over time, although the Washington Post recently opted for columns to show scores for Iraq and Afghanistan. One drawback is that we're used to associating upward-sloping trend lines with positive changes, and in Freedom House's index higher scores actually mean less freedom. If you keep an ascending scale on the y axis, it might take readers a moment to realize a downward dip in scores is really a good thing.

When I was in graduate school I made a lot of these:

I liked this approach because the inverted y-axis values give gains in freedom an upward-sloping line. The colored regions show clearly whether a country is classified as "Free," "Partly Free" or "Not Free" without leaving the reader to interpret the scores. If I were making this chart today, I might leave the scores off the y axis entirely since they draw attention to Freedom House's methodology when the real take-away is the trend line. But, if you're really interested in how Freedom House rated Ukraine each year, the scores are there to see.

Back to the chart at the top of the post. Like everything on this blog, it's an experiment. Instead of an up-and-down trend line (does freedom go up and down? I guess it does when you assign scores to it), I wanted to try showing different levels of freedom by color only. The red-yellow-green scheme is widely recognized and familiar — green is good, red is not good, yellow is somewhere in the middle.

It's still hard to graph Freedom House's index without some explanation of the scoring methodology. See all the notes I added to the top chart just to feel like I was being thorough? And they don't even go into all the changes Freedom House has made to its methodology over the years.

One thing I might have done differently: The green, yellow and red areas on this chart don't correspond exactly to Freedom House's "Free," "Partly Free" and "Not Free" classifications. Freedom House's "Partly Free" rating encompasses scores of 3.0 to 5.0. On my chart, 3.0 is still pretty green and the true yellow doesn't show up until 4.0. Looking at it now, I feel it might be more important to show the three broad classifications more clearly than to show a continuous and symmetrical color gradient.

Data Source: Freedom House Freedom in the World data, 1972-2012.

Chart Tools: Adobe Illustrator (top chart), Microsoft Excel and Word.

For Fun: Half Marathon

View larger

On Sunday I ran my first half marathon at the Alexandria Running Festival. It was a beautiful, cool, sunny morning, and I managed a time of 2:04:18. I've never been a running superstar, so I was really pleased. A big thanks to all of the event organizers and volunteers for putting on a great race and keeping the energy up on the course.

As race day approached, I was struck by just how small a component of running a half marathon the actual race is. Don't get me wrong — running 13.1 miles is daunting, particularly for someone who hasn't raced in a few years. But the vast majority of the hard work, stress, anticipation and strategy come weeks and months earlier.

The chart above shows the full half marathon: the 13.1 miles I ran on Sunday plus the 12 weeks of training that made the final 13.1 possible. I liked the idea of arranging the data in a circle rather than a linear time-series chart, mostly because training process is very cyclical. Each week has a pattern of long, short and mid-distance runs, and once the final race is finished it's time to start gearing up for the next challenge (for me, it's the Marine Corps Marathon's Run Amuck on June 8). Plus, I thought the circle would look cool.

To create this chart in Illustrator, I first made two standard column charts using the Chart feature, one each for the distance and pace-per-mile data. Then I copied the individual columns onto a grid of circular "spokes" that I drew manually (if there's a way to have Illustrator generate a grid like this, I'd love to learn it!). The concentric rings showing the mile scale for the distance data and the minute scale for the time data were drawn to fit the columns, rather than the other way around. Overlapping the distance and time columns meant I overlapped the scales as well. It's a little crowded there at the center of the chart, but I hope it works.

Data Source: Personal records
Chart Tool: Adobe Illustrator

Extra Credit — Budget Variations

View larger

I'm a fan of Google's interactive charts and tables, and I think the ones in the last post turned out pretty well. The ability to scroll over a line or column segment to see more data is especially handy for packing in the details while keeping the chart clean.

Even with that great feature, some of the budget data were still hard to display — particularly in the smaller spending categories that are hard to find when you're mousing over. So I tossed the data in Adobe Illustrator so I could have a little more flexibility with the design. It's still hard to read in spots, but it's nice to have control over the labels and segment colors.

Illustrator also lets me add a few design flourishes, like these paths highlighting the redistribution of budget outlays among spending categories:

View larger

Data Sources:2014 - H.Con.Res. 25 PCS, (113th Congress); 2012 - H.Con.Res. 34 (112th Congress); 2000 - H.Con.Res. 68 ENR (106th Congress). Accessed through THOMAS between May 14, 2013, and May 20, 2013.

Chart Tool: Adobe Illustrator

Assignment 1: Show the Data — U.S. Federal Budget

There have been a lot of stories coming out of Washington lately, and the federal budget really hasn't been one of them. That will likely change soon. As of May 15 Congress can begin considering appropriations bills for the 2014 fiscal year, meaning between now and September we can expect to hear more about how much money federal agencies will have to spend in the coming year.

Despite its seemingly unlimited pockets, Congress is required to abide by specific spending limits each year. Who sets these limits? The President's Budget gets a lot of attention when it's released each February (or April as was the case this year), but these budget recommendations are just that — recommendations. Congress actually sets its own spending limits with an annual budget resolution, usually passed in April.

By law, once the president has released a recommended budget, both the Senate and the House of Representatives draw on that document and their own priorities to draft separate budget resolutions. Once each house approves its own resolution, they swap notes and hammer out their differences in a report that becomes a binding outline of next year's spending. The final budget resolution is the basis for appropriations bills that portion out money to specific agencies.

Of course nothing's straightforward in the Congress, and lawmakers have failed to agree on a final budget resolution for the last three fiscal years. A budget resolution for 2014 also appears to be dead in the water. 

So how much does Congress have to spend in 2014? Well, it depends where you look.

Fiscal Year 2014 Outlays by Category (in millions of dollars)
Technically, when Congress fails to pass a budget resolution the previous year's resolution remains in effect. The last successful budget resolution was Senate Concurrent Resolution 13 (S.Con.Res. 13 ENR). It was passed for the 2010 fiscal year but includes spending levels for 2011 through 2014. In years when no final budget resolution is passed, the House sometimes formally adopts its own resolution as binding for the purposes of making appropriations.

The charts above show spending levels for 2014 outlined in S.Con.Res. 13 alongside those proposed by the House and the Senate in separate resolutions this spring. None of these is a definitive guideline for next year's appropriations, but it's fun to compare them.

It's also fun to compare spending levels for each category over time.

Notice how Homeland Security got its own spending category in 2005. The Overseas Contingency Operations/Global War on Terror category was originally called Overseas Deployments and Other Activities when it showed up in the 2008 budget.

U.S. Federal Budget Outlays by Category, 2000-2012 (in millions of dollars)

Data Sources: 2014 - S.Con.Res. 13 ENR (111th Congress), H.Con.Res. 25 PCS, (113th Congress); S.Con.Res. 8 ES (113th Congress); 2012 - H.Con.Res. 34 (112th Congress); 2011 - H.Res. 1493 (111th Congress); 2010 - S.Con.Res. 13 ENR (111th Congress); 2009 - S.Con.Res. 70 ENR (110th Congress); 2008 - S.Con.Res. 21 ENR (110th Congress); 2007 - H.Con.Res. 376 EH (109th Congress); 2006 - H.Con.Res. 95 ENR (109th Congress); 2005 - S.Con.Res. 95 (108th Congress); 2004 - H.Con.Res. 95 ENR (108th Congress); 2003 - H.Con.Res. 353 EH (107th Congress); 2002 - H.Con.Res. 83 ENR (107th Congress); 2001 - H.Con.Res. 290 ENR (106th Congress); 2000 - H.Con.Res. 68 ENR (106th Congress).
Accessed through THOMAS between May 14, 2013, and May 20, 2013.

Chart Tool: Google Docs

What's going on here?

Welcome to Drawing Tables. This blog is a “learning experiment” — a chance to play around with data visualization techniques and programs while building up some additional design skills. I hope to dive into a wide range of policy areas and bring a little creative perspective to numbers and data. Most importantly, I hope to have fun.

Because I work best with a little structure, I’ll be drawing on Edward Tufte’s The Visual Display of Quantitative Information and a few other sources to create a kind of syllabus to guide the design projects. I’ll explore different chart types, graphing and design software, and best practices for information design.

Who am I? I’m a former journalist, a policy wonk, writer, editor, researcher, graphic designer and sometime photographer always looking for new ways to tell a story. I’m also a chronic perfectionist, which I hope to challenge at least a little bit with this blog. Design is hard. Data is tricky. I’m learning as I go, and things could get a little ugly.

And that’s going to be OK.

— Laura