Data Mashups in R
A Case Study in Real-World Data Analysis
Publisher: O'Reilly Media
Final Release Date: March 2011
Pages: 40

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
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O'Reilly MediaData Mashups in R
 
3.3

(based on 4 reviews)

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Pros

  • Concise (3)

Cons

    Best Uses

    • Intermediate (4)

    Reviewed by 4 customers

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    2.0

    Obsolete as soon it came out the door.

    By Cahuamero

    from Seattle, WA

    About Me Aspiring Data Scientist, Developer, Educator

    Verified Reviewer

    Pros

    • Novel Topic
    • Timely Subject

    Cons

    • Obsolete Examples
    • Too many errors

    Best Uses

    • Intermediate

    Comments about O'Reilly Media Data Mashups in R:

    It's not really the authors' fault, but both Yahoo and the US Census Bureau changed their data structures and web services after this book came out. This rendered the examples almost unworkable.
    If you want to get through the examples, you will have to figure out how to work the new Yahoo web services.
    It would be helpful if the authors could post some sort of update.

     
    4.0

    Data Mashups in R

    By Peter

    from Portland, OR

    About Me Maker

    Pros

    • Concise
    • Easy to understand
    • Helpful examples

    Cons

      Best Uses

      • Expert
      • Intermediate

      Comments about O'Reilly Media Data Mashups in R:

      This book presents an interesting project, drawing together a number of data sources and geocoding them. Following the code step by step, as the project develops. The code as written required some debugging. To their credit this debugging seems to be due to some changes made by yahoo (read the documentation carefully). This book pointed me in the the right directions. In the process I learned a great deal about using regular expressions, xml, and shapefiles.

       
      4.0

      Good Programmers starting for R

      By Rob

      from Brisbane, Australia

      About Me Developer

      Verified Reviewer

      Pros

      • Accurate
      • Concise
      • Easy to understand

      Cons

        Best Uses

        • Intermediate

        Comments about O'Reilly Media Data Mashups in R:

        The Book Data Mashups in R gives a short tutorial using R to pull data from the web and analyse it. The specific presentation is looking at foreclosure auctions in Philadelphia. I used this book to get some practical hands on exposure to R. It happily fulfilled this use case for me, exposing packages in R, and helping me gain an idea of how R can be used. It also provided a good idea as to what R does well, helping me know when to pull the R tool out of the shed.

        I recommend the book to experienced developers who want to get their heads around what is possible with R and how R works by trying it out.

        [this book was reviewed as a part of the O'Reilly Blogger Review Program]

        (3 of 4 customers found this review helpful)

         
        3.0

        Binding data sources in R

        By Michal Konrad Owsiak

        from Poland

        Verified Reviewer

        Pros

        • Accurate
        • Concise

        Cons

        • Too condese

        Best Uses

        • Expert
        • Intermediate

        Comments about O'Reilly Media Data Mashups in R:

        Have you ever wondered whether R can utilize regular expressions? Have you been forced to download data from particular source before you start using it within R? Or maybe you were not quite sure how to deal with XML within R scripts. Well, thats what Data Mashups are all about. Jeremy and Xiao-Yi show you how to deal with all these aspects. They show it in very condense way, but still, you can get the feeling what's R and scripting is all about. You will find here regular expressions, XML parsing, how to use PBSmapping package and description of how to combine all of this within single project.

        The book is quite interesting – in terms of the topic. However, it looks little bit messy. I would expect that you get the idea of the problem we want to solve before you start solving it. Well, not this time. Jeremy and Xiao-Yi skip this part and jump straight into solution. It complicates the process of getting through the ideas presented in the book. I prefer to be offered problem before I start looking for a solution. Question here is – maybe for this kind of topic, essay is really enough. I don't know. I am still getting through R and it's "traps", and honestly, I choose other R related titles from O'Reilly over Data Mashups. If you start your adventure with R choose "R Cookbook" or "25 Recipes for Getting Started with R". If you are already familiar with R, and you want to go beyond what can be called standard, go ahead with Data Mashups.

        Idea of the book is very good. The application, not the best one. I can value the solutions and the code snippets that are shown – you can always reuse them at some point in your own projects, however, the way everything is bound and presented doesn't quite appeal to me.

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