Data Mashups in R

✍ Scribed by Jeremy Leipzig, Xiao-Yi Li

• Publisher: O'Reilly Media
• Year: 2011
• Tongue: English
• Leaves: 38
• Edition: 1
• Category: Library

✦ Synopsis

How do you use R to import, manage, visualize, and analyze real-world data? With this short, hands-on tutorial, you learn how to collect online data, massage it into a reasonable form, and work with it using R facilities to interact with web servers, parse HTML and XML, and more. Rather than use canned sample data, you'll plot and analyze current home foreclosure auctions in Philadelphia. This practical mashup exercise shows you how to access spatial data in several formats locally and over the Web to produce a map of home foreclosures. It's an excellent way to explore how the R environment works with R packages and performs statistical analysis.Parse messy data from public foreclosure auction postings Plot the data using R's PBSmapping package Import US Census data to add context to foreclosure data Use R's lattice and latticeExtra packages for data visualization Create multidimensional correlation graphs with the pairs() scatterplot matrix package

✦ Table of Contents

Table of Contents......Page 7
Introduction......Page 9
Messy Address Parsing......Page 11
Exploring “streets”......Page 13
Obtaining Latitude and Longitude Using Yahoo......Page 14
Shaking the XML Tree......Page 15
The Many Ways to Philly (Latitude)......Page 16
Using Internal Class Methods......Page 17
The Unmappable Fake Street......Page 18
Taking Shape......Page 19
PBSmapping......Page 20
Developing the Plot......Page 21
Preparing to Add Points to Our Map......Page 22
Exploring R Data Structures: geoTable......Page 24
Turning Up the Heat......Page 25
Factors When You Need Them......Page 26
Filling with Color Gradients......Page 27
Importing Census Data......Page 29
Descriptive Statistics......Page 32
Descriptive Plots......Page 33
Correlation......Page 35
Final Thoughts......Page 36
Quick and Dirty Essentials of R......Page 37
O’Reilly Resources......Page 38