Python Programming Language
Math Adventures With Python: An Illustrated Guide to Exploring Math With Code
Math Adventures With Python
An Illustrated Guide to Exploring Math With Code
Paperback      ISBN: 1593278675
"Teaches math concepts through programming. Begins with a crash course in basic programming concepts and how to use Python's built-in Turtle module, and then explores topics like writing programs to solve equations and matrices, drawing polygons and fractals, and using the Processing graphics library to create interactive 2D and 3D models"--
Serious Python: Black-Belt Advice on Deployment, Scalability, Testing, and More
Serious Python
Black-Belt Advice on Deployment, Scalability, Testing, and More
Paperback      ISBN: 1593278780
Collects practical tips and real-world advice for tackling common Python problems and taking your code to the next level and features interviews with high-profile Python developers who share their tips, tricks, best practices, and real-world advice gleaned from years of experience. Original.
Beginning Programming With Python for Dummies
Beginning Programming With Python for Dummies
2nd Edition    Paperback      ISBN: 1119457890
The easy way to learn programming fundamentals with Python Python is a remarkably powerful and dynamic programming language that's used in a wide variety of application domains. Some of its key distinguishing features include a very clear, readable syntax, strong introspection capabilities, intuitive object orientation, and natural expression of procedural code. Plus, Python features full modularity, supporting hierarchical packages, exception-based error handling, and modules easily written in C, C++, Java, R, or .NET languages, such as C#. In addition, Python supports a number of coding styles that include: functional, imperative, object-oriented, and procedural. Due to its ease of use and flexibility, Python is constantly growing in popularity—and now you can wear your programming hat with pride and join the ranks of the pros with the help of this guide. Inside, expert author John Paul Mueller gives a complete step-by-step overview of all there is to know about Python. From performing common and advanced tasks, to collecting data, to interacting with package—this book covers it all! - Use Python to create and run your first application - Find out how to troubleshoot and fix errors - Learn to work with Anaconda and use Magic Functions - Benefit from completely updated and revised information since the last edition If you've never used Python or are new to programming in general, Beginning Programming with Python For Dummies is a helpful resource that will set you up for success.
Beginning Python: Using Python 2.6 and Python 3.1
Beginning Python
Using Python 2.6 and Python 3.1
Paperback      ISBN: 0470414634
Explains the basics of quickly developing Web and scientific applications, incorporating databases, and mastering systems tasks on various operating systems, in a guide that also covers basic scripts and standard modules in specific program development domains. Original.

Complex Network Analysis in Python: Recognize - Construct - Visualize - Analyze - Interpret
Complex Network Analysis in Python
Recognize - Construct - Visualize - Analyze - Interpret
Paperback      ISBN: 1680502697
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.
Cracking Codes With Python: An Introduction to Building and Breaking Ciphers
Cracking Codes With Python
An Introduction to Building and Breaking Ciphers
Paperback      ISBN: 1593278225
In Cracking Codes with Python, you’ll learn how to program in Python while making and breaking ciphers, which are used to encrypt secret messages. (No programming experience required!). After a quick crash course in programming, you’ll make, test, and hack classic cipher programs. You’ll begin with simple programs like the Caesar cipher and then work your way up to public key cryptography and the RSA cipher, which is used for modern secure data transmissions. Each program comes with the full code and a line-by-line explanation of how things work. By book’s end, you’ll walk away with a solid foundation in Python and same crafty programs under your belt. Learn how to: -Combine loops, variables, and flow control statements into real working programs -Use dictionary files to instantly detect whether text is English or nonsense -Create programs to test that the code you've written is working correctly -Write your own programming modules that you can import and use in other programs -Debug your programs and find common errors Cracking Codes with Python is a chance to pick up some Python skills while getting a peek into the intriguing world of cryptography—what more could an aspiring hacker want?
Data Wrangling with Python
Data Wrangling with Python
Paperback      ISBN: 1491948817
Digging into data does not have to be painful. With Data Wrangling Using Python, you'll learn how to clean and analyze data, create compelling stories, and scale that data as necessary. There are awesome discoveries to be made in unassuming datasets and stories to be told. You don
Deep Learning with Python
Deep Learning with Python
Paperback      ISBN: 1617294438
Introduces the field of deep learning using the Python language and the Keras library, covering such topics as setting up a deep-learning environment, image-classification models, and neural style transfer, text generation, and image generation.
Derivatives Analytics With Python: Data Analysis, Models, Simulation, Calibration and Hedging
Derivatives Analytics With Python
Data Analysis, Models, Simulation, Calibration and Hedging
Hardcover      ISBN: 1119037999
"Supercharge options analytics and hedging using the power of Python Derivatives Analytics with Python shows you how to implement market-consistent valuation and hedging approaches using advanced financial models, efficient numerical techniques, and thepowerful capabilities of the Python programming language. This unique guide offers detailed explanations of all theory, methods, and processes, giving you the background and tools necessary to value stock index options from a sound foundation. You'll find and use self-contained Python scripts and modules and learn how to apply Python to advanced data and derivatives analytics as you benefit from the 5,000+ lines of code that are provided to help you reproduce the results and graphics presented. Coverage includes market data analysis, risk-neutral valuation, Monte Carlo simulation, model calibration, valuation, and dynamic hedging, with models that exhibit stochastic volatility, jump components, stochastic short rates, and more. The companion website features all code and IPython Notebooks for immediate execution and automation. Python is gaining ground in the derivatives analytics space, allowing institutions to quickly and efficiently deliver portfolio, trading, and risk management results. This book isthe finance professional's guide to exploiting Python's capabilities for efficient and performing derivatives analytics. Reproduce major stylized facts of equity and options markets yourself Apply Fourier transform techniques and advanced Monte Carlo pricing Calibrate advanced option pricing models to market data Integrate advanced models and numeric methods to dynamically hedge options Recent developments in the Python ecosystem enable analysts to implement analytics tasks as performing as with C or C++, but using only about one-tenth of the code or even less. Derivatives Analytics with Python -- Data Analysis, Models, Simulation, Calibration and Hedging shows you what you need to know to supercharge your derivatives and risk analytics efforts"--

Effective Computation in Physics
Effective Computation in Physics
Paperback      ISBN: 1491901535
Effective Computation in Physics is a handy guide to the types of problems you run into with computational physics—such as version control, bash scripts, object orientation, large databases, and parallel machines. The authors provide detailed scientific computing motivations, clear and concise tutorials, and references to further information about each of the topics presented. This book fills the existing training gap for students and scientists who conduct physics in a world where simulations have replaced desktop experiments and sophisticated data traversing algorithms have replaced pen and paper analysis. - Provides a central source that ties various pieces of computational physics together - Contains coverage of the Python programming language aimed toward physicists - Helps you properly analyze and compellingly visualize your data - Includes chapters on hot topics like NumPy and HDF5