Data Mashups in R
1st Edition
Published on 5. June 2009
29 pages
978-0-596-80477-0 (ISBN)
Description
This article demonstrates how the realworld data is imported, managed, visualized, and analyzed within the R statistical framework. Presented as a spatial mashup, this tutorial introduces the user to R packages, R syntax, and data structures. The user will learn how the R environment works with R packages as well as its own capabilities in statistical analysis. We will be accessing spatial data in several formats-html, xml, shapefiles, and text-locally and over the web to produce a map of home foreclosure auctions and perform statistical analysis on these events.
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Content
- Intro
- Messy Address Parsing
- Exploring "streets"
- Obtaining Latitude and Longitude Using Yahoo
- Shaking the XML Tree
- The Many Ways to Philly (Latitude)
- Using Data Structures
- Using Helper Methods
- Using Internal Class Methods
- Exceptional Circumstances
- The Unmappable Fake Street
- No Connection
- Taking Shape
- Finding a Usable Map
- PBSmapping
- Developing the Plot
- Preparing to Add Points to Our Map
- Exploring R Data Structures: geoTable
- Making Events of our Foreclosures
- Turning Up the Heat
- Factors When You Need Them
- Filling with Color Gradients
- Statistics of Foreclosure
- Importing Census Data
- Descriptive Statistics
- Descriptive Plots
- Correlation Revisited
- Final Thoughts
- Appendix: Getting Started
- Obtaining R
- Quick and Dirty Essentials of R
