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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 developed for data scientists.� It describes strategies and approaches for extracting data from HTML, XML, and JSON formats and how to programmatically access data from the Web.�
Along with these general skills, the authors illustrate several applications that are relevant to data scientists, such as reading and writing spreadsheet documents both locally and via Google Docs, creating interactive and dynamic visualizations, displaying spatial-temporal displays with Google Earth, and generating code from descriptions of data structures to read and write data.� These topics demonstrate the rich possibilities and opportunities to do new things with these modern technologies.� The book contains many examples and case-studies that readers can use directly and adapt to their own work.� The authors have focused on the integration of these technologies with the R statistical computing environment.� However, the ideas and skills presented here are more general, and statisticians who use other computing environments will also find them relevant to their work.
Deborah Nolan is Professor of Statistics at University of California, Berkeley.
Duncan Temple Lang is Associate Professor of Statistics at University of California, Davis and has been a member of both the S and R development teams.
- Sales Rank: #1006761 in Books
- Published on: 2013-11-29
- Original language: English
- Number of items: 1
- Dimensions: 9.90" h x 1.20" w x 7.00" l, 2.90 pounds
- Binding: Paperback
- 663 pages
From the Back Cover
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 developed for data scientists.� It describes strategies and approaches for extracting data from HTML, XML, and JSON formats and how to programmatically access data from the Web.�
Along with these general skills, the authors illustrate several applications that are relevant to data scientists, such as reading and writing spreadsheet documents both locally and via GoogleDocs, creating interactive and dynamic visualizations, displaying spatial-temporal displays with Google Earth, and generating code from descriptions of data structures to read and write data.� These topics demonstrate the rich possibilities and opportunities to do new things with these modern technologies.� The book contains many examples and case-studies that readers can use directly and adapt to their own work.� The authors have focused on the integration of these technologies with the R statistical computing environment.� However, the ideas and skills presented here are more general, and statisticians who use other computing environments will also find them relevant to their work.
Deborah Nolan is Professor of Statistics at University of California, Berkeley.
Duncan Temple Lang is Associate Professor of Statistics at University of California, Davis and has been a member of both the S and R development teams.
About the Author
Deborah Nolan is Professor of Statistics at University of California, Berkeley.
Duncan Temple Lang is Associate Professor of Statistics at University of California, Davis and has been a member of both the S and R development teams.
Most helpful customer reviews
12 of 12 people found the following review helpful.
Comprehensive, encyclopedic and accessible
By Nicholas Horton
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.
6 of 8 people found the following review helpful.
Massive book (650+ pages) with color coded code, diagrams, and with excellent examples
By JIR
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 "
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