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If you’re concerned about the US economy, you probably caught last week’s news that Standard & Poor’s Case–Shiller home price index for 20 large cities continued to decline in January. If you’re curious to know more about recent housing trends in the US, you can not only ask Wolfram|Alpha about the 20-city index, but also for details on any of the major metropolitan areas included in that composite. For example, query “Las Vegas, Phoenix, Los Angeles, Miami Case–Shiller index”, and you can see just how big the housing “bubble” was in each of these four cities.
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Since Wolfram|Alpha‘s launch in May 2009, one of its most talked-about features has been its ability to compute specific answers to questions about math, chemistry, economics, demographics, and much more. But as its knowledge base continues to grow, it’s also able to highlight interesting and useful connections between data sets, and to reveal information that you might not think to ask for on your own.
One of the coolest examples of this is our recently enhanced relocation calculator. For several months, we’ve been able to answer simple questions about the relative cost of living in various United States cities and metropolitan areas. If you told Wolfram|Alpha that you were relocating from Seattle to Miami with a salary of $35000, you’d get a comparison of the relative cost of groceries, housing, and other expenses in each city, plus an estimate of the salary required to maintain a comparable standard of living in your destination city. On its own, this is a useful little calculator—but it’s also something that dozens of other websites could do.
But because Wolfram|Alpha knows tons of other details about any given city, our relocation calculator can now do things that no other site can. In addition to salary and cost-of-living comparisons, you now get comparisons of each city’s population, median home sale prices, unemployment rates, crime rates, sales taxes, traffic congestion, and climate—a useful sampling of current and historical comparative data for anyone contemplating a move.
We’ll highlight similar enhancements as they are released. And as always, we welcome your suggestions for new data, or new ways of looking at existing data, in any domain covered by Wolfram|Alpha.
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When we launched Wolfram|Alpha in May 2009, it already contained trillions of pieces of information—the result of nearly five years of sustained data-gathering, on top of more than two decades of formula and algorithm development in Mathematica. Since then, we’ve successfully released a new build of Wolfram|Alpha’s codebase each week, incorporating not only hundreds of minor behind-the-scenes enhancements and bug fixes, but also a steady stream of major new features and datasets.
We’ve highlighted some of these new additions in this blog, but many more have entered the system with little fanfare. As we near the end of 2009, we wanted to look back at seven months of new Wolfram|Alpha features and functionality.