Apr 24, 2012 · 5:45 PM
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For our April meeting: This month's talk is going to look at the geo-spatial capabilities of R. We'll look at how to import common geographical data formats into R and some of the free geographic data sources and map layers available. We'll then look at how to create maps in R using this data, and some of the ways to style it to display our data. We'll look at how R stores geographic data and how we can perform queries against that - for example identifying which points fall into a particular region. Finally, we'll take a brief look at modeling geospatial data and some of the issues to be aware of.
About the Speaker: Daniel Marlay who is a senior manager in Ernst & Young's Actuarial team where he has worked for the last 5 years building their business analytics capability. Daniel has a degree in Physics & Astronomy and worked for 7 years in various data Analytics roles consulting to the marketing industry prior to working at Ernst & Young. He has used R extensively in his work over the last 8 years and has recently been investigating the use of R for geospatial analyses.