ARTICLES
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Negative online reviewers make a lot more errors than positive ones.
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A survey of 17,000 women about sexiness, body shaming, and confidence.
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How often to do the teams behind top cryptocurrencies update their codebase?
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We built a tool to help you make and embed data tables.
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Ranking which countries get work done (and which ones don't).
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We analyze the financial net worth of young professionals by age, gender, occupation and more.
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How many San Francisco startups also have offices somewhere else? 38%.
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Ranking the household products that pollute your home the most (and least).
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Work gets done at 11AM on a Monday in October. At all other times of day, we're basically slacking from our most productive.
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Analyzing real estate data from Houston to see if landlords increased rents after Hurricane Harvey.
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Ranking which sites discount the most using coupon codes.
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The places in America where you'll spend a lot of your income on rent. And places where you won't.
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When do people get sick and when do doctors get busy? It depends if you're visiting a pediatrician or a proctologist.
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Ranking the cities and states and release the most toxins into the environment.
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We analyzed the font usage patterns of Americans to answer a very important question - who likes Comic Sans?
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Who is the most influential memer on the Internet and each social network?
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Compared to other technical fields, there are fewer women and under-represented minorities studying data science today.
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Ranking the cities and states where pizza is most expensive and prevalent.
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Data confirms what you may already know - people hate being left waiting at the doctor's office.
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What's the most popular snack at offices in America? LaCroix sparkling water!
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We analyze how much money people actually spend on food and whether they actually get meals, groceries, and ingredients delivered.
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People are 81% more likely to fill out a form if they're on their desktop computers instead of phones.
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Who smiles at work? Ranking countries, companies, and job titles by propensity to smile.
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Do neighborhoods with lots of coffee shops tend to have high rent?
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Data that answers the most important question for people who sell things online - what causes potential customers to open their wallets?