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Relaunched: Use population data to identify promising markets

Capital One is not your typical bank. We were founded in 1994, with the big idea of using analytics to provide customized products to consumers. But we didn’t stop there - Capital One is now one of the nation's 10 largest banks. Since big data and technology have been a huge part of our identity from the beginning, we are pushing the limits of mobile platforms, transaction processing, cyber security, and many other technical fields.

One project we're currently focused on is auto loans. In order to target high-potential customers, we'd like to use publicly available population census data coupled with our internal proprietary analytics. The first step is to identify metropolitan areas experiencing higher than average growth. This is often a sign of favorable financial circumstances and bigger purchases.

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top 10
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submissions
DONE
35 months ago
Deliverables

Using the U.S. Census data below, write a script in Java, Python, C/C++, or Javascript that calculates the following metrics:

1) Top five cities to target based on highest population growth (% change) between 2010-2012. (50,000 population minimum)

2) Top five cities to avoid based on the most shrinking population (% change) between 2010-2012. (50,000 population minimum)

3) Top five states with highest cumulative growth (combined across all metropolitan areas) between 2010-2012.

Additional Materials:
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This challenge has received 62 submissions
Top 5 share 7500 Next 5 share 2500
1500 N The University of Memphis
1500 Square pic yo Loyola University Chicago
1500 A California Institute of Technology
1500 Square pic 1625510 735690359783503 1971741631 n University of Washington
1500 Square pic img 7925 University of Waterloo
500 M Johns Hopkins University
500 Square pic 1016221 3522665870870 1252840112 n Duke University
500 Square pic profile University of Missouri - Columbia
500 Square pic fractal California Polytechnic State University
500 A California Polytechnic State University
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