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Data science and complex networks : real cases studies with Python

By: Caldarelli, Guido.
Contributor(s): Chessa, Alessandro [Co- author].
Material type: materialTypeLabelBookPublisher: New York Oxford University Press 2016Description: viii, 130 p.ISBN: 9780199639601.Subject(s): Computer networks | Big data | Python - computer program language | System analysisDDC classification: 003.72 Summary: This book provides a comprehensive yet short description of the basic concepts of complex network theory and the code to implement this theory. Differently from other books, we present these concepts starting from real cases of study. The application topics span from food webs, to the Internet, the World Wide Web, and social networks, passing through the international trade web and financial time series. The final part is devoted to definition and implementation of the most important network models. We provide information on the structure of the data and on the quality of available datasets. Furthermore, we provide a series of codes to implement instantly what is described theoretically in the book. People knowing the basis of network theory could learn the art of coding in Python by checking our codes and using the online material. In particular, the interactive Python notebook format is used so that the reader can immediately experiment by themselves with the codes present in the manuscript. To this purpose we have set up a dedicated web site where readers can download and test the codes. The whole project is finalised to allow scientists and practitioners the possibility of working instantly in the field of complex networks. http://www.oxfordscholarship.com/view/10.1093/acprof:oso/9780199639601.001.0001/acprof-9780199639601?rskey=hJ12zO&result=3
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Non-fiction 003.72 C2D2 (Browse shelf) Checked out 14/12/2019 194563

This book provides a comprehensive yet short description of the basic concepts of complex network theory and the code to implement this theory. Differently from other books, we present these concepts starting from real cases of study. The application topics span from food webs, to the Internet, the World Wide Web, and social networks, passing through the international trade web and financial time series. The final part is devoted to definition and implementation of the most important network models. We provide information on the structure of the data and on the quality of available datasets. Furthermore, we provide a series of codes to implement instantly what is described theoretically in the book. People knowing the basis of network theory could learn the art of coding in Python by checking our codes and using the online material. In particular, the interactive Python notebook format is used so that the reader can immediately experiment by themselves with the codes present in the manuscript. To this purpose we have set up a dedicated web site where readers can download and test the codes. The whole project is finalised to allow scientists and practitioners the possibility of working instantly in the field of complex networks.



http://www.oxfordscholarship.com/view/10.1093/acprof:oso/9780199639601.001.0001/acprof-9780199639601?rskey=hJ12zO&result=3

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