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Created July 10, 2012 12:00
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Crime Crunchers Intro

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Welcome to Crime Crunchers! ======================== Time to Crunch Crime!

Crime Crunchers was started in the city of San Antonio by a group of concerned citizens who are dedicated to using data science to lower the property crime & theft rates in San Antonio. Crime Crunchers is an effort to develop methods and deliver data that predict areas and times in the city likely to experience increased negative activity. We focus not on profiling individuals but discovering signals of negative activity found in open data.

Crime Crunchers aims to be a place where anyone can be the super hero without the burden of looking good in matching tights or developing the next generation gadgetry. Anyone with the drive to code and crunch numbers or learn more about data science are invited to participate. Our goal is to be a positive force multiplier of good in our beautiful city of San Antonio through education and awarness of data methods to watch our neighborhoods.

Crime Crunchers is a grass roots effort, many of our members (though very geeky) are not versed in all facets of the data processing pipline. This documentation is a series of basic data science tutorials to help foster productivity within the community of concerned citizens. Most tutorials initially will be in the Python programming language. You are welcome to contribute new and parallel material in any language you choose.

TUTORIALS:

Finding Data

Extracting Data

Exploring Data

Time Data

Geo Data

Streams of Data

Data of Networks

Big Data

GUIDES:

Neighbohood Watch

Freedom of Information Act

Databases

Programming Languages

Spatio Temporal Statistics

DATA SOURCES:

Calls For Service

Geo Tagging

Maps

Interesting: ----------- Hotspot Policing: http://www.sacpd.org/newsroom/releases/liveview.aspx?release_id=20110213-029

Seattle Crime Maps:

http://www.seattle.gov/police/crime/onlinecrimemaps.htm

DOJ: Crime Mapping https://www.ncjrs.gov/html/nij/mapping/index.html

DOJ: Hot Spots https://www.ncjrs.gov/pdffiles1/nij/209393.pdf

PROJECTS:

Parse PDFs

Load Data into sql

Load Data into NoSQL

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