Cargando…
Complex network analysis in Python : recognize - construct - visualize - analyze - interpret /
Construct, analyze, and visualize networks with networkx, a Python language module. Network analysis is a powerful tool you can apply to a multitude of datasets and situations. Discover how to work with all kinds of networks, including social, product, temporal, spatial, and semantic networks. Conve...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
[Place of publication not identified] :
The Pragmatic Bookshelf,
[2018]
|
| Colección: | Pragmatic programmers.
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
| LEADER | 00000cam a2200000 i 4500 | ||
|---|---|---|---|
| 001 | OR_on1028639841 | ||
| 003 | OCoLC | ||
| 005 | 20231017213018.0 | ||
| 006 | m o d | ||
| 007 | cr unu|||||||| | ||
| 008 | 180314s2018 xx a ob 000 0 eng d | ||
| 040 | |a UMI |b eng |e rda |e pn |c UMI |d STF |d TOH |d OCLCF |d CEF |d KSU |d OCLCQ |d DEBBG |d G3B |d S9I |d UAB |d OCLCQ |d DST |d OCLCO |d OCLCQ |d OCLCO | ||
| 020 | |a 9781680502695 | ||
| 020 | |a 1680502697 | ||
| 020 | |a 1680505416 | ||
| 020 | |a 9781680505412 | ||
| 020 | |z 9781680505412 | ||
| 029 | 1 | |a GBVCP |b 1016523874 | |
| 035 | |a (OCoLC)1028639841 | ||
| 037 | |a CL0500000946 |b Safari Books Online | ||
| 050 | 4 | |a QA76.73.P98 | |
| 082 | 0 | 4 | |a 658.1554 |2 23 |
| 049 | |a UAMI | ||
| 100 | 1 | |a Zinoviev, Dmitry, |e author. | |
| 245 | 1 | 0 | |a Complex network analysis in Python : |b recognize - construct - visualize - analyze - interpret / |c by Dmitry Zinoviev. |
| 264 | 1 | |a [Place of publication not identified] : |b The Pragmatic Bookshelf, |c [2018] | |
| 264 | 4 | |c Ã2018 | |
| 300 | |a 1 online resource (1 volume) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a data file | ||
| 490 | 1 | |a The Pragmatic programmers | |
| 588 | 0 | |a Online resource; title from title page (viewed March 12, 2018). | |
| 500 | |a "Version: P1.0 (January 2018)." | ||
| 504 | |a Includes bibliographical references. | ||
| 520 | |a Construct, analyze, and visualize networks with networkx, a Python language module. Network analysis is a powerful tool you can apply to a multitude of datasets and situations. Discover how to work with all kinds of networks, including social, product, temporal, spatial, and semantic networks. Convert almost any real-world data into a complex network--such as recommendations on co-using cosmetic products, muddy hedge fund connections, and online friendships. Analyze and visualize the network, and make business decisions based on your analysis. If you're a curious Python programmer, a data scientist, or a CNA specialist interested in mechanizing mundane tasks, you'll increase your productivity exponentially. Complex network analysis used to be done by hand or with non-programmable network analysis tools, but not anymore! You can now automate and program these tasks in Python. Complex networks are collections of connected items, words, concepts, or people. By exploring their structure and individual elements, we can learn about their meaning, evolution, and resilience. Starting with simple networks, convert real-life and synthetic network graphs into networkx data structures. Look at more sophisticated networks and learn more powerful machinery to handle centrality calculation, blockmodeling, and clique and community detection. Get familiar with presentation-quality network visualization tools, both programmable and interactive--such as Gephi, a CNA explorer. Adapt the patterns from the case studies to your problems. Explore big networks with NetworKit, a high-performance networkx substitute. Each part in the book gives you an overview of a class of networks, includes a practical study of networkx functions and techniques, and concludes with case studies from various fields, including social networking, anthropology, marketing, and sports analytics. Combine your CNA and Python programming skills to become a better network analyst, a more accomplished data scientist, and a more versatile programmer. What You Need: You will need a Python 3.x installation with the following additional modules: Pandas (>=0.18), NumPy (>=1.10), matplotlib (>=1.5), networkx (>=1.11), python-louvain (>=0.5), NetworKit (>=3.6), and generalizesimilarity. We recommend using the Anaconda distribution that comes with all these modules, except for python-louvain, NetworKit, and generalizedsimilarity, and works on all major modern operating systems. | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Python (Computer program language) | |
| 650 | 0 | |a Network analysis (Planning) |x Computer programs. | |
| 650 | 6 | |a Python (Langage de programmation) | |
| 650 | 7 | |a Network analysis (Planning) |x Computer programs |2 fast | |
| 650 | 7 | |a Python (Computer program language) |2 fast | |
| 830 | 0 | |a Pragmatic programmers. | |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9781680505399/?ar |z Texto completo (Requiere registro previo con correo institucional) |
| 994 | |a 92 |b IZTAP | ||