Complex Network Analysis In Python

Complex Network Analysis in Python

Complex Network Analysis in Python

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.

Pandas Brain Teasers

This book contains 25 short programs that will challenge your understanding of Pandas. Like any big project, the Pandas developers had to make some design decisions that at times seem surprising. This book uses those quirks as a teaching opportunity. By understanding the gaps in your knowledge, you'll become better at what you do. Some of the teasers are from the author's experience shipping bugs to production, and some from others doing the same. Teasers and puzzles are fun, and learning how to solve them can teach you to avoid programming mistakes and maybe even impress your colleagues and future employers. Working with data is central to nearly everything we do, from disease contact tracing and analyzing health records to smart meters that track utility consumption behavior. With the power of Python's pandas library, you can process and analyze this data in a highly efficient and simple-to-understand way. And with 25 brain teasers designed to turn this technology's quirks into a teaching opportunity, you'll be honing your data science skills while having fun at the same time. Following a simple format, you'll challenge yourself and your understanding of pandas. Read a short Python program that uses pandas, try to guess the output, run the code yourself, and then go to the next page for an explanation of the solution. From common pitfalls and hidden gotchas to unexpected twists and turns, you'll deepen your understanding of pandas, learn to write more efficient code, and reduce the number of bugs in the software you develop. You may even impress your colleagues and your employers, both present and future. Learn the tricks of the trade with Python's pandas, in one of the most fun and creative ways around. What You Need: To run the code you'll need Python version 3.8 or upper and Pandas version 1.0 or upper installed. We use Python version 3.8.3 and Pandas version 1.0.5; the output might change in future versions.