Chris Wilson

Check out this chart and search tool to see the political leanings of the places that Starbucks, Walmart, and 2,700 other companies call home

If you live near a Ben & Jerry’s or a few Dunkin’ Donuts outposts, odds are good that your Congressional district elected a Democrat on Tuesday. More familiar with the inside of a Pizza Hut or a Long John Silver’s? Chances are you’ll be represented next year by a Republican.

The following chart places 49 common brands on a political spectrum based on the percentage of their brick-and-mortar stores that are located in Democratic or Republican districts. To do this, TIME matched nearly 2 million store locations provided by the research company AggData to their corresponding Congressional district and then tallied them by that district’s vote in 2014 midterms. Of the 139 American Apparel stores, for example, 83 percent are in blue districts. Nearly nine in 10 Belk department stores, meanwhile, can be found in red districts. All the other brands on the chart fall somewhere in between. You can look for any store you like in the search tool below the graphic.

There is no evidence, of course, that a regular infusion of banana ice cream and fudge chunks inspires a person toward liberalism. Because two-thirds of the Ben & Jerry’s in the United States are found in Democratic districts, however, the mere presence of a store in a district raises the statistical odds that its residents are people who vote for Democrats.

While stores like Whole Foods or Hobby Lobby might already conjure partisan stereotypes, the vast majority of America’s brands do not. Even so, where these stores are located tells us a tremendous amount about who their shoppers are sending to Washington.

Methodology

The list of retail locations was provided by AggData. Stores were matched to Congressional district by comparing their longitude and latitude to the Census definitions of districts. The results do not include the 14 Congressional races that have yet to be resolved as of 6:00 AM on Nov. 6, 2014.

Read next: How the World Sees America Now

Correction: The interactive chart originally linked the incorrect record for Armani Exchange when the user clicked the icon in the chart. It has since been updated.

Despite growing numbers of candidates, they almost never even succeed as spoilers by throwing the race to one candidate or another.

Almost no one seriously thinks that Sean Haugh will be the next senator from North Carolina. But political observers in both major parties are worried that the pizza deliveryman and Libertarian candidate could siphon enough votes to sway the election, likely to be one of the closest in the country on Tuesday. And stakes couldn’t be higher: any one election could determine control of the Senate in 2015.

But which party has more to fear from Haugh? Kentucky Senator Rand Paul campaigned for Republican nominee Thom Tillis in early October, a move seen as an attempt to shore up Libertarian-leaning Republican voters. More recently, the American Future Fund, a conservative outside spending group, bet $225,000 that Haugh could flip the election in the Republicans’ with an ad campaign focused on his unembarrassed enthusiasm for marijuana, aimed to draw away younger supporters of Democratic incumbent Kay Hagan.

Though Haugh is currently polling at around 5 percent—more than the margin between Tillis and Hagan—he is very unlikely to spoil anything other than the hopes of a few misled pot smokers. While the threat of spoiler candidates makes for breathless headlines and titillating front-page reads, the real odds of this happening are extremely slim.

For starters, it is very rare for a Congressional contest to be decided by a margin small enough for a third-party candidate to make a difference. Of the 1,873 elections that TIME examined—every House and Senate race going back to 2006, not including special elections and runoffs—only 70 were won with less than 50 percent of the vote. A Libertarian candidate ran in 46 of them.

The threat of a spoiler candidate is further exaggerated by the common assumption that third-party voters would otherwise turn up at the polls at all.

“That’s the old style to think about voting,” says Stanford professor Jon Krosnick, a social psychologist and polling expert. “We’ve now come to recognize that the candidates influence turnout. The presence of the third-party candidate can lure people to vote who otherwise wouldn’t have voted at all.”

It’s impossible to know with any precision how people would have behaved without the presence of a third-party candidate. Even asking them in polls is unreliable, given that pollsters typically report unrealistically high turnout figures when they ask people if they voted.

The picture is confounded yet further by the fact that a distaste for the major parties is often the motivation that draw a person to a third-party candidate in the first place.

That’s a view shared by Emily Salvette, who drew 10,630 votes as a Libertarian in the 2012 race for Michigan’s 1^st District. “I do honestly think that a lot of people wouldn’t have voted,” she says. “They’re not engaged anymore because they don’t like the choice.” The Republican in that contest, Congressman Dan Benishek, edged out his Democratic challenger by 1,881 votes.

Depending whose base you think Salvette drew from, you might call her either a spoiler or nearly one. But Salvette says she saw support from voters with a variety of viewpoints, including people who supported her views on everything from medical marijuana to gun rights.

This is where the spoiler math falls apart: 1,881 votes doesn’t seem like a large share of Salvette’s 10,630. But to tip the election to the Democrat, every single one of the people who voted for Salvette would have had to show up had Salvette not been in the race—very unlikely—and they would have had to break for the Democrat by a sizable margin of 59-41. The fewer voters that show up, the larger that margin needs to be.

Of course, it is typically the Republican candidate who feels more threatened by a Libertarian in the race.

“Republicans think that the Libertarian vote comes out of their column,” says University of Virginia political scientist Larry Sabato. In fact, there’s evidence from exit polls in the 2013 Virginia governor’s race that Libertarian Robert Sarvis, who garnered 145,762 votes in a race decided by about 55,000, drew more support from winner Terry McAuliffe, the Democrat, than from Republican Ken Cuccinelli. The majority of Sarvis’ supporters said they otherwise would not have voted.

It’s certainly possible to find more compelling cases for spoilers. In 2012, Democrat Jim Matheson beat challenger Mia Love in Utah’s 4th District by 768 votes, while Libertarian Jim Vein received 6,439 votes—and earned some unkind attention from Republicans before the votes were fully counted. Even so, half of Vein’s voters would have needed to show up without him in the race, those supporters would have had to vote for Love over Matheson by at least a 61-39 margin to make a difference.

Even the most famous supposed spoiler in modern history–the 2000 presidential election in Florida–is less clear-cut than most of us recall. One statistical analysis of polls and ballot returns suggests that Nader’s supporters would only have broken for Gore over Bush by a 60-40 margin, if they broke for either candidate. That many of Nader’s supporters would otherwise have turned out and supported either major-party candidate is far from established.

When an election is that close, blaming a third-party candidate is the electoral equivalent of blaming Bill Buckner for spoiling the 1986 World Series for the Boston Red Sox: It is merely the most visible excuse for a loss that could have been reversed if one of a thousand factors had gone just a little better.

The cost of running for Congress has increased more than 500 percent since 1984. Here's an interactive look at how campaign expenditures have outrun inflation, health care, and even the rising cost of college

The NBC affiliate in Des Moines, Iowa, added an hour to its nightly newscast this year to profit from all the political ads ahead of the Nov. 4 midterm elections, but demand was still too great. “There is only so much inventory I have,” explains WHO-TV station manager Dale Woods. It is the same in tight races all across the country. Nearly bottomless campaign and super-PAC bank accounts have been unloaded on airtime, mailings and get-out-the-vote efforts. And in recent years, the spending growth has accelerated.

Since the mid-1980s, the amount dumped on elections by campaigns and outside groups, as measured by the Federal Election Commission, has grown 555 percent—faster than even the alarming increases in the costs of health care and private college tuition. The reasons, say political scientists, include growth in the national economy, the razor-thin margin determining congressional control and changes to campaign-finance rules. Expect the trend to continue. Senate races in North Carolina and Kentucky this year could cost more than $100 million, and the estimated spending on TV ads in Alaska and Iowa already tops $11 per eligible voter.

Methodology

Sources for interactive: Federal Election Commission summary files; Centers for Medicare and Medicaid Services; U.S. Census Bureau; St. Louis Fed; National Center for Education Statistics. Outside spending data for the years 2006-2012, which are missing from FEC summary reports, are courtesy of the Center for Responsive Politics.

The total value of an election is calculated in two parts: Campaign spending and outside spending. Campaign spending consists of all expenditures except authorized transfers of funds to other committees, as well as party-coordinated spending, and includes primary elections. Outside Spending encompasses third-party expenditures that are made without the knowledge or consent of the candidates, but only includes transactions that are explicitly used to advocate for or against a candidate.

Answer these 13 questions and find out

In his book Happy City, Charles Montgomery offers evidence that where you live has a powerful effect on how you feel. From our commutes to our neighbors and our daily routines, where we choose to live can influence our feelings in ways most of us never imagine.

The following quiz will ask you 13 questions about your life. After answering each one, you’ll see how thousands of others have answered the same question. This survey will help us reveal new insights about the relationship between cities and happiness. All responses are completely anonymous.

The quiz was developed by Montgomery, Chris Barrington-Leigh of McGill University, along with TIME.

The data for average happiness scores will update as more readers take the survey. Current results based on 3,302 respondents. Data may also be used for a future study by Barrington-Leigh on happiness across the United States.

Read next: What Your Zip Code Says About You

Channel your inner Gryffindor to figure out Rowling's latest puzzle

Speculation is swirling after Harry Potter author J.K. Rowling tweeted a mysterious phrase that appears to be a scrambled message. Hogwarts fans are jumping at the idea that she could be hinting at another novel set in the wizarding world.

Use TIME’s anagram solver to see if you can figure it out. Then share your best guess. The winner gets 50 points for Gryffindor.

Here’s the full Twitter exchange.

Use this search tool to find out

Doctors received $3.5 billion from pharmaceutical companies and device makers over a five month period in 2013, according to figures the federal government released this week. The massive dataset includes 4.2 million individual payments made to physicians (including dentists) for things like meals, consulting fees and royalty payments for devices they have helped invent. The new data includes 360,000 doctors by name.

In the days leading up the release of the information, physician groups mobilized to argue that the data, which the 2010 Affordable Care Act mandates be disclosed, is incomplete and misleading. For their part, the Centers for Medicare and Medicaid Services, which oversaw the release, states that, “Just because there are financial ties doesn’t mean that anyone is doing anything wrong.” CMS withheld the names of the recipients on 40 percent of the payments over concerns about data quality.

Using the following tool, you can search for any physician in the database by last name and see any gifts, consulting fees, paid travel, or other payment he or she received between August and December of 2013.

Critics of this sort of disclosure are quick to point out that there are many positive benefits to relationships between drug and device companies, which produce new life-saving treatments every year, and the doctors who get those treatments to patients who need them. Meanwhile, some research suggests that even cursory relationships with industry do affect a doctor’s behavior.

Among those doctors who were identified, orthopedic surgeons were by far the most compensated. They account for 11 of the 18 physicians who received over $1 million over the five covered months in the data:

While the reason for the prominence of orthopedic surgeons at the top of the list varies for each doctor, orthopedic surgery often involves cutting edge devices for things like knee and hip replacements, many of which are exceedingly expensive. In some cases, doctors are receiving thousands of dollars in royalties for these devices because they have a stake in the intellectual property rights. (This is separate from owning part a stake in the company itself, which is reported separately.)

The picture of which pharmaceutical company pays doctors the most is less clear because payments are often recorded under the name of the subsidiary company making the payment. DePuy Synthes, a subsidiary of Johnson & Johnson that manufactures orthopedic and neurosurgery devices, tops the list of companies making payments to doctors during the period with $34.5 million. Arthrex, Inc., a manufacturer of orthopedic surgical supplies, came in second with $15.5 million. Astra Zeneca and Pfizer are also among the top 10 with $15.3 million and $10.01 million respectively. This analysis does not include anonymized payments.

Of all payments, $109 million is documented as “compensation for services other than consulting, including serving as faculty or as a speaker at a venue other than a continuing education program.” Consulting fees accounted for $91 million. Food and beverages accounted for $57.4 million, and travel and lodging accounted for $45 million. Because the disclosures require that the location of travel be disclosures, we are able to build a picture of where companies like to fly doctors for conferences, speeches, meetings, and other events:

Data that was withheld because of unresolved disputes will be published in future disclosures.

Use this calculator to find out

The latest Census data on American incomes drove home a troubling fact: people aren’t making as much as they once did. The median household income in the United States in 2013 was $51,939, down 8 percent from 2007 when adjusted for inflation. Though the recession technically ended several years ago, large numbers of people continue to suffer from flat wages and rising prices.

But while the middle class continues to suffer, many slices of the population are doing better. Using individual-level Census data for 2008 to 2012—15 million records in total—TIME crunched the numbers for every demographic by gender, age, education and marital status.

The following calculator will tell you how your salary stacks up and how that’s changed over time. (The information you enter is not recorded. In fact, it never leaves your computer.)

These charts show individual personal income—money respondents received from any source—and only include people who worked full-time in a given year. (While unemployment was a tremendous scourge during the recession and its aftermath, including it here would confound an analysis of how income has changed.)

Since 2008, incomes have increased by 5.1 percent among all surveyed, while inflation rate over that time was 6.6 percent, according to the Bureau of Labor Statistic figures. (In other words, if your income increased by less than 6.6 percent, you lost purchasing power over that period.) But not all groups are falling behind. Married women between ages 41-50 with professional degrees saw a 16.6 percent growth in income over the past five years, the largest gain of any subset of the population for which there were at least 1000 respondents in the data. At the opposite end of the spectrum, men between 22 and 25 with some college education but no degree saw their income fall by 16.7 percent.

Gender

Women are recovering from the recession slightly faster than men, though men make considerably more overall.

Age

Americans in their 20s saw the highest cut to their salaries since 2008.

Education

Those with less education have recovered the slowest, if at all.

Marital Status

Single Americans are generally younger than other demographics shown here. This is consistent with median income changes by age.

Methodology

The inputs for the calculator are determined by Census categories for gender, age, educational attainment, and marital status. The data was extracted from the Integrated Public Use Microdata Series project (full citation below). IPUMS aggregates individual-level responses from the Census Bureau’s American Community Survey, an annual sampling of 1 percent of the population. The complete codebook for the extract, which can be used to recreate the complete dataset, is available here.

The analysis is limited to those who were at least 18 years old and coded as a “5” or a “6” in the WKSWORK2 column, meaning they worked at least 48 weeks of the previous 12 months. To allow for a sufficient sample size, individual years of age were bucketed into the ranges displayed in the interactive. Some similar educational levels and marital statuses were also combined.

Once the data was bucketed and grouped by unique combinations of demographic traits—married women from 51-64 with an associate’s degree, for example—we took the median of all of their incomes. This involved first accounting for the fact that not every person has equal weight in the sample. IPUMS provides a PERWT variable. After adding each person to the pool a number of times equal to his or her statistical weight, we took the median of the pooled values. In almost all cases, this “weighted median” was very similar to a naïve median calculated by considering each respondent to have equal weight.

Figures were then spot checked by replicating this process from the raw data in two different computational platforms, R and Mathematica. Any subpopulation with fewer than 50 respondents is not included.

Citation

Miriam King, Steven Ruggles, J. Trent Alexander, Sarah Flood, Katie Genadek, Matthew B. Schroeder, Brandon Trampe, and Rebecca Vick. Integrated Public Use Microdata Series, Current Population Survey: Version 3.0. [Machine-readable database]. Minneapolis: University of Minnesota, 2010.

As Scotland votes for independence, a look at the shifting lines that have divided the region's countries since 1900

Voting is now underway in Scotland to determine whether to cut ties with the United Kingdom. Should Scots vote to do so, they would become the last country to bedevil cartographers as the national boundaries in Europe continue to shift at a regular pace. The above map displays Europe’s border changes from the past 114 years, stretching back into the Ottoman Empire.

Methodology

The years in the timeline were chosen to reflect each major shift in borders after wars or other geopolitical events. Maps prior to 1946 were provided by the Max Planck Institute for Demographic Research, maps after 1946 provided by The Geography of the International System: The CShapes Dataset.

Superheroes save June. Princesses reign in May. And Nazis usually invade in February. Here's a visual guide to strange patterns that populate the big screen

What do you call a thong-clad scientist paired with a chainsaw-toting cheerleader? Answer: the perfect summer movie.

It’s no secret that the movies follow an unofficial calendar: Summer is for action heroes and explosions, while dark themes and delicate plots visit in the winter, readying for the Oscars. But what about some of the less familiar patterns that popular Hollywood seasons? To study the secrets of the cinema calendar, TIME gathered data on the 8,298 movies in IMDB that made at least $100,000 in inflation-adjusted dollars, all the way back to 1913. By correlating the keywords for each movie to the month that it was released, we were able to find highly seasonal topics for each month of the year.

For all the highs and lows of the Hollywood calendar, check out this chart.

Some of the more surprising highlights: People are saddest in January. The tag “melancholy” is most popular in the beginning of the year. See “Sideways” and “The Hours.” February is a great month for World War II. “Nazis” too. Drug lords come out in the summer. August to be specific. In fact, the second-highest grossing movie of the moment is Lucy, in which a woman (Scarlet Johansson) works as a mule for a Korean drug kingpin.December is lethal for main characters. That’s when they die most often. See “Titanic.”

Methodology

The keywords on IMDB are submitted by users so the data is not perfectly consistent, but across thousands of movies one sees clear and sensible pattern. Each keyword was measured according to the total number of movies it appeared in each month of the calendar year, regardless of which year the movie appeared. These figures where then converted to percentages according to the keyword’s total volume. Since movies come out in different volumes in different months–October is a particularly popular type to release a film regardless of topic, for example–the data was then normalized according to the total number of films released in a given month.

An interactive demonstration of how the justice system uses data to determine the length of prison sentences

When deciding how long to send someone to jail, many states currently use statistical models to determine whether offenders risk committing a future crime if they are let out on probation or parole. In the past several years, researchers have been able to demonstrate that factors like drug and alcohol problems, family life and education can help them predict the likelihood of recidivism.

In a speech before the National Association of Criminal Defense Lawyers Friday, Attorney General Eric Holder warned that this increasingly popular use of data-based methods in determining prison sentences “may run the risk of imposing drastically different punishments for the same crimes.” As Holder told TIME this week, he fears that the statistical methods that punish for factors like education will disproportionately affect minority and poor offenders.

Below, you’ll find a demonstration of the kind of kind calculator many states use to predict odds of recidivism. Change the responses in the following interactive to see how the odds of re-arrest change with the offender’s circumstances. In many states, these odds are being used to determine sentencing lengths.

The actual use of this “post conviction risk assessment” varies widely. This method, developed by criminal justice researcher Christopher T. Lowenkamp and colleagues, is an area of ongoing study. Using standard statistical models, the researchers were able to study a large population of offenders to determine which factors can predict a person’s likelihood of future offense and which cannot. Notably, a person’s race–left in this interactive for demonstration purposes–has almost no predictive power over future behavior when all other factors are held constant. In other words, a white offender and black offender with the same answers to the above questions are almost equally likely to commit a future crime.