XML and Web Technologies for Data Sciences with R

  • Deborah Nolan
  • Duncan Temple Lang

Part of the Use R! book series (USE R)

Table of contents

  1. Front Matter
    Pages i-xxiv
  2. Data Formats: XML and JSON

    1. Front Matter
      Pages 1-3
    2. Deborah Nolan, Duncan Temple Lang
      Pages 5-18
    3. Deborah Nolan, Duncan Temple Lang
      Pages 19-52
    4. Deborah Nolan, Duncan Temple Lang
      Pages 53-74
    5. Deborah Nolan, Duncan Temple Lang
      Pages 75-113
    6. Deborah Nolan, Duncan Temple Lang
      Pages 115-182
    7. Deborah Nolan, Duncan Temple Lang
      Pages 183-225
    8. Deborah Nolan, Duncan Temple Lang
      Pages 227-253
  3. Web Technologies Getting Data from the Web

    1. Front Matter
      Pages 255-258
    2. Deborah Nolan, Duncan Temple Lang
      Pages 259-313
    3. Deborah Nolan, Duncan Temple Lang
      Pages 315-338
    4. Deborah Nolan, Duncan Temple Lang
      Pages 339-379
    5. Deborah Nolan, Duncan Temple Lang
      Pages 381-401
    6. Deborah Nolan, Duncan Temple Lang
      Pages 403-439
    7. Deborah Nolan, Duncan Temple Lang
      Pages 441-461
  4. General XML Application Areas

    1. Front Matter
      Pages 463-466
    2. Deborah Nolan, Duncan Temple Lang
      Pages 467-500
    3. Deborah Nolan, Duncan Temple Lang
      Pages 501-535
    4. Deborah Nolan, Duncan Temple Lang
      Pages 537-580

About this book

Introduction

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.

Keywords

HTML JSON document R XML data science data visualization with R

Authors and affiliations

  • Deborah Nolan
    • 1
  • Duncan Temple Lang
    • 2
  1. 1.University of CaliforniaBerkeleyUSA
  2. 2.University of CaliforniaDavisUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4614-7900-0
  • Copyright Information Springer Science+Business Media New York 2014
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-1-4614-7899-7
  • Online ISBN 978-1-4614-7900-0
  • Series Print ISSN 2197-5736
  • Series Online ISSN 2197-5744
  • About this book