xml web technologies data (26 resultados)

XXIV, 663 p. Softcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Use R! Sprache: Englisch.

Condición: Fair. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. Clean from markings. In fair condition, suitable as a study copy. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1500grams, ISBN:9781461478997.

Condición: New. In.

Condición: New.

PF. Condición: New.

Condición: Good. Almost like new but with very few cosmetic defects.

Condición: Sehr gut. Zustand: Sehr gut | Seiten: 663 | Sprache: Englisch | Produktart: Bücher.

Condición: New.

Condición: New.

Paperback. Condición: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

Condición: New. pp. xxiv + 663.

Condición: New.

Paperback. Condición: Brand New. 2014 edition. 685 pages. 9.90x7.00x1.50 inches. In Stock.

Paperback. Condición: new. Paperback. 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. Web technologies are increasingly relevant to scientists working with data, for both accessing data and creating rich dynamic and interactive displays. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback. Condición: Like New. Like New. book.

Paperback. Condición: new. Excellent Condition.Excels in customer satisfaction, prompt replies, and quality checks.

Condición: As New. Unread book in perfect condition.

PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Data integration is the process of facilitating the access to data residing at multiple heterogeneous data sources, and providing users and applications with a unified view of these data. Data integration is crucial in enterprises that store and exchange data in disparate and incompatible formats, and is one of the big challenges of the World Wide Web, where millions of heterogeneous data sources are available. This book contributes to different aspects of the design of modern data integration systems in the context of the Web. On one hand, the work contributes to the Semantic Integration research trend, which refers to the problem of reconciling data from autonomous sources using ontologies and other semantic-based tools. The work suggests a novel solution to XML-RDF semantic integration and also contributes to the problem of Ontology Alignment, defining a rigorous and scalable semantic similarity measure for RDF labelled directed graphs. On the other hand, the book suggests a novel solution to the problem of translating a user query (targeting a logical mediated schema), into queries over a set of autonomous data sources provided with restricted web interfaces.

Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Data integration is the process of facilitating the access to data residing at multiple heterogeneous data sources, and providing users and applications with a unified view of these data. Data integration is crucial in enterprises that store and exchange da.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 663 pp. Englisch.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Covers important modern Web technologies from the R perspectiveDescribes over 30 R packages developed by the authorsComprehensive examples show how to interface with many applications, Web services and data formatsWeb technologie.

Condición: New. Print on Demand pp. xxiv + 663 65 Illus. (51 Col.).

Condición: New. PRINT ON DEMAND pp. xxiv + 663.