Data Mashups in R

A Case Study in Real-World Data Analysis

Nonfiction, Computers, Advanced Computing, Programming, Data Modeling & Design
Cover of the book Data Mashups in R by Jeremy Leipzig, Xiao-Yi Li, O'Reilly Media
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Author: Jeremy Leipzig, Xiao-Yi Li ISBN: 9781449307257
Publisher: O'Reilly Media Publication: March 4, 2011
Imprint: O'Reilly Media Language: English
Author: Jeremy Leipzig, Xiao-Yi Li
ISBN: 9781449307257
Publisher: O'Reilly Media
Publication: March 4, 2011
Imprint: O'Reilly Media
Language: English

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
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

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