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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. 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.

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Practical Programming, Third Edition: An Introduction to Computer Science Using Python 3.6

Classroom-tested by tens of thousands of students, this new edition of the best-selling intro to programming book is for anyone who wants to understand computer science. Learn about design, algorithms, testing, and debugging. Discover the fundamentals of programming with Python 3.6—a language that’s used in millions of devices. Write programs to solve real-world problems, and come away with everything you need to produce quality code. This edition has been updated to use the new language features in Python 3.6.

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Python Testing with pytest: Simple, Rapid, Effective, and Scalable

Do less work when testing your Python code, but be just as expressive, just as elegant, and just as readable. The pytest testing framework helps you write tests quickly and keep them readable and maintainable—with no boilerplate code. Using a robust yet simple fixture model, it’s just as easy to write small tests with pytest as it is to scale up to complex functional testing for applications, packages, and libraries. This book shows you how.

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Data Science Essentials in Python: Collect → ​Organize​ → ​Explore​ → ​Predict​ → Value​

Go from messy, unstructured artifacts stored in SQL and NoSQL databases to a neat, well-organized dataset with this quick reference for the busy data scientist. Understand text mining, machine learning, and network analysis; process numeric data with the NumPy and Pandas modules; describe and analyze data using statistical and network-theoretical methods; and see actual examples of data analysis at work. This one-stop solution covers the essential data science you need in Python.

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Practical Programming (2nd edition): An Introduction to Computer Science Using Python 3

This book is for anyone who wants to understand computer programming. You’ll learn to program in a language that’s used in millions of smartphones, tablets, and PCs. You’ll code along with the book, writing programs to solve real-world problems as you learn the fundamentals of programming using Python 3. You’ll learn about design, algorithms, testing, and debugging, and come away with all the tools you need to produce quality code. In this second edition, we’ve updated almost all the material, incorporating the lessons we’ve learned over the past five years of teaching Python to people new to programming.