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  • Book Overview & Buying Network Science with Python
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Network Science with Python

Network Science with Python

By : David Knickerbocker
5 (15)
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Network Science with Python

Network Science with Python

5 (15)
By: David Knickerbocker

Overview of this book

Network analysis is often taught with tiny or toy data sets, leaving you with a limited scope of learning and practical usage. Network Science with Python helps you extract relevant data, draw conclusions and build networks using industry-standard – practical data sets. You’ll begin by learning the basics of natural language processing, network science, and social network analysis, then move on to programmatically building and analyzing networks. You’ll get a hands-on understanding of the data source, data extraction, interaction with it, and drawing insights from it. This is a hands-on book with theory grounding, specific technical, and mathematical details for future reference. As you progress, you’ll learn to construct and clean networks, conduct network analysis, egocentric network analysis, community detection, and use network data with machine learning. You’ll also explore network analysis concepts, from basics to an advanced level. By the end of the book, you’ll be able to identify network data and use it to extract unconventional insights to comprehend the complex world around you.
Table of Contents (17 chapters)
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1
Part 1: Getting Started with Natural Language Processing and Networks
5
Part 2: Graph Construction and Cleanup
9
Part 3: Network Science and Social Network Analysis

Data visualization

There are several Python libraries that can be used for data visualizations. Matplotlib is a good place to start, but other libraries such as Seaborn can create more attractive visualizations, and Plotly can create interactive visualizations.

Matplotlib

Matplotlib is a Python library for data visualization. That’s it. If you have data, Matplotlib can probably be used to visualize it. The library is integrated directly into pandas, so if you use pandas, you likely also use Matplotlib.

Matplotlib has a very steep learning curve and is not intuitive at all. I consider it a necessary evil if you are learning about Python data science. No matter how much data visualization I do with Matplotlib, it never becomes easy, and I memorize very little. I say all of this not to badmouth Matplotlib, but so that you will not feel negativity toward yourself if you struggle with the library. We all struggle with the library.

Setup

As with pandas and NumPy, if...

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Network Science with Python
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