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Review XML and Web Technologies for Data Sciences with R Use R by Deborah Nolan Duncan Temple Lang

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Web technologies are increasingly relevant to scientists working with data, for both accessing data and creating rich dynamic and interactive displays.  The XML and JSON data formats are widely used in Web services, regular Web pages and JavaScript code, and visualization formats such as SVG and KML for Google Earth and Google Maps.  In addition, scientists use HTTP and other network protocols to scrape data from Web pages, access REST and SOAP Web Services, and interact with NoSQL databases and text search applications.  This book provides a practical hands-on introduction to these technologies, including high-level functions the authors have

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Book ID Asin: 1461478995
Book Title: XML and Web Technologies for Data Sciences with R (Use R!)
Book Author: Deborah Nolan,Duncan Temple Lang
Book Format and Price:
Book Format Name: Kindle
Book Format Price: $28.22-$104.49
Book Format Name: Paperback
Book Format Price: $3.99-$109.99
Book Price: $109.99
Book Category: Books, Science & Math, Mathematics and unknown
Book Rating: 5 ratings

XML and Web Technologies for Data Sciences with R (Use R!) by Deborah Nolan,Duncan Temple Lang Book Review

Name: JIR
Rating: 5.0 out of 5 stars
Title: .0 out of 5 stars Massive book (650+ pages) with color coded code, diagrams, and with excellent examples
Date: Reviewed in the United States on April 22, 2014
Review: I love this book so far, this is why it gets the 5 stars, the content and detail in explaining looks awesome. It has awesome examples and it walks you through many examples used to retrieving and meaningfully using information from the web (in whichever form it comes - XML, JSON, HTML tables, etc, etc). I think the next edition should take this into consideration:
1. Readers are lazy, and want to grab an example and start in the page they open the book at. Even though it is the right thing to do, I don't want to go back 3 pages to figure out I have to load the XML library for example. Even if the example repeats information available in the page before, every example should be self contained.
2. Readers are lazy: I didn't like I had to spend an extra couple of minutes figuring out where the data came from, even though in the Preface you tell us that the data is in a folder on your website (rxmlwebtech).
3. The authors use "=" instead of "<-" to assign stuff in R. I am by no means a purist or anything like that, but it took me a while to learn to use "<-" and it kind of hurts my eyes to see the "=" used instead. I am sure the authors have a reason for using "=", but as I said, I am lazy and didn't take the time to read the book from start, I am only going to the examples that I want to use.

Name: Nicholas Horton
Rating: 5.0 out of 5 stars
Title: .0 out of 5 stars Comprehensive, encyclopedic and accessible
Date: Reviewed in the United States on January 10, 2014
Review: There's been huge interest in ways of accessing larger datasets and more sophisticated analyses in recent years, but the tools have been poorly documented and few examples are available. Nolan and Temple Lang's text is a massive (663 page) effort to bridge this gap and make web technologies and reproducible workflows available to a much larger audience. The first part of the book introduces readers to XML and JSON (assuming no prior knowledge). Part two focuses on web scraping (automating data access) from html and databases. The final part of the book presents four in-depth examples in R.

I hope to be able to teach a "case studies in data science" course using this text, and applaud the authors for their efforts to help ensure that statisticians and analysts have the tools needed to help use data to make better decisions.