Hello again.

Since my last update, I have collected all the demographic data that I will be using for this project. The IPUMS database from NHGIS proved invaluable in this task and I am indebted to that service. The data I collected are organized by census tracts, which are geographical divisions within counties that the census uses for greater geographic granularity. The data have attributes for race, gender, age, income, and a few more things that will allow me to analyze trends throughout the Atlanta region.

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The necessary preliminary procedure for any data analysis project is data collection and compilation. So it is for my project, which is to determine the impact of distance from home on college football player performance. Fortunately, the website 247sports.com has a fairly complete database of recruits, as well as their rating, position, hometown, and college. Unfortunately, the website has this information in a very unfriendly format for data scraping. The major challenge of this first segment was implementing a program that took those attributes from the website and created a spreadsheet with this information in a workable format (Microsoft Excel). I successfully implemented this program and created the necessary databases by utilizing the BeautifulSoup module in Python to scrape the data from the website, as well as the xlwt package to write it out to Excel.

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