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| 008 | 150903s2014 xxu| o |||| 0|eng d | ||
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_a9781461479000 _99781461479000 |
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| 024 | 7 |
_a10.1007/9781461479000 _2doi |
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| 035 | _avtls000342326 | ||
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_a201509030851 _bVLOAD _c201405050242 _dVLOAD _y201402061123 _zstaff |
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_aMX-SnUAN _bspa _cMX-SnUAN _erda |
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| 050 | 4 | _aQA276-280 | |
| 100 | 1 |
_aNolan, Deborah. _eautor _9320882 |
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| 245 | 1 | 0 |
_aXML and Web Technologies for Data Sciences with R / _cby Deborah Nolan, Duncan Temple Lang. |
| 264 | 1 |
_aNew York, NY : _bSpringer New York : _bImprint: Springer, _c2014. |
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| 300 |
_axxiv, 663 páginas 65 ilustraciones, 51 ilustraciones en color. _brecurso en línea. |
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| 336 |
_atexto _btxt _2rdacontent |
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| 337 |
_acomputadora _bc _2rdamedia |
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| 338 |
_arecurso en línea _bcr _2rdacarrier |
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| 347 |
_aarchivo de texto _bPDF _2rda |
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| 490 | 0 |
_aUse R!, _x2197-5736 |
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| 500 | _aSpringer eBooks | ||
| 505 | 0 | _aData Formats XML and JSON -- Web Technologies, Getting Data from the Web -- General XML Application Areas -- Bibliography -- General Index -- R Function and Parameter Index -- R Package Index -- R Class Index -- Colophon. | |
| 520 | _aWeb 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. | ||
| 590 | _aPara consulta fuera de la UANL se requiere clave de acceso remoto. | ||
| 700 | 1 |
_aTemple Lang, Duncan. _eautor _9320883 |
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| 710 | 2 |
_aSpringerLink (Servicio en línea) _9299170 |
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| 776 | 0 | 8 |
_iEdición impresa: _z9781461478997 |
| 856 | 4 | 0 |
_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-1-4614-7900-0 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL) |
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