Numerical Python, 2nd Edition
Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to Jupyter projects, demonstrates how to numerically compute solutions and mathematically model applications in big data, cloud computing, financial engineering, business management and more.
Numerical Python, Second Edition, presents many brand-new case study examples of applications in data science and statistics using Python, along with extensions to many previous examples. Each of these demonstrates the power of Python for rapid development and exploratory computing due to its simple and high-level syntax and multiple options for data analysis.
After reading this book, readers will be familiar with many computing techniques including array-based and symbolic computing, visualization and numerical fi ...
Python Data Analytics, 2nd Edition
Explore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific computing with NumPy visualization with matplotlib, and machine learning with scikit-learn.
This revision is fully updated with new content on social media data analysis, image analysis with OpenCV, and deep learning libraries. Each chapter includes multiple examples demonstrating how to work with each library. At its heart lies the coverage of pandas, for high-performance, easy-to-use data structures and tools for data manipulation.
Python for Data Analysis, 2nd Edition
Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You'll learn the latest versions of pandas, NumPy IPython, and Jupyter in the process.
Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It's ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub.
Use the IPython shell and Jupyter notebook for exploratory computing; Learn basic and advanced features in NumPy (Numerical Python); Get started with data analysis tools in the pandas library; Use flexible tools to load, clean, transform, merge, and reshape data; Create informative visualizations ...
NumPy Cookbook, 2nd Edition
NumPy has the ability to give you speed and high productivity. High performance calculations can be done easily with clean and efficient code, and it allows you to execute complex algebraic and mathematical computations in no time.
This book will give you a solid foundation in NumPy arrays and universal functions. Starting with the installation and configuration of IPython, you'll learn about advanced indexing and array concepts along with commonly used yet effective functions. You will then cover practical concepts such as image processing, special arrays, and universal functions. You will also learn about plotting with Matplotlib and the related SciPy project with the help of examples. At the end of the book, you will study how to explore atmospheric pressure and its related techniques. By the time you finish this book, you'll be able to write clean and fast code with NumPy. ...
NumPy, 3rd Edition
In today's world of science and technology, it's all about speed and flexibility. When it comes to scientific computing, NumPy tops the list. NumPy will give you both speed and high productivity. This book will walk you through NumPy with clear, step-by-step examples and just the right amount of theory. The book focuses on the fundamentals of NumPy including array objects, functions, and matrices, each of them explained with practical examples. You will then learn about different NumPy modules while performing mathematical operations such as calculating the Fourier transform, finding the inverse of a matrix, and determining eigenvalues, among many others. This book is a one-stop solution to knowing the ins and outs of the vast NumPy library, empowering you to use its wide range of mathematical features to build efficient, high-speed programs. ...
IPython Notebook Essentials
In data science, it is difficult to present interesting visual or technical content, as it involves scientific notations that are not easy to type in a normal document format. IPython provides a web-based UI called Notebook, which creates a working environment for interactive computing that combines code execution with computational documents. IPython Notebook makes the task simpler as it was developed for scientific programming to solve larger problems through a series of smaller programs. IPython Notebook is used to learn Python in a fun and interactive way and to do some serious parallel / technical computing.
The book begins with an introduction to the efficient use of IPython Notebook for interactive computation. The book then focuses on the integration of technologies such as matplotlib, pandas, and SciPy. The book is aimed at empowering you to work with IPython Notebook for interactive computing, configuring it, creating your own notebooks / research documents. You will learn ...
Learning NumPy Array
NumPy is an extension of Python, which provides highly optimized arrays and numerical operations. NumPy replaces a lot of the functionality of Matlab and Mathematica specifically vectorized operations, but in contrast to those products is free and open source. In today's world of science and technology, it is all about speed and flexibility.
This book will teach you about NumPy a leading scientific computing library. This book enables you to write readable, efficient, and fast code, which is closely associated to the language of mathematics. Save thousands of dollars on expensive software, while keeping all the flexibility and power of your favorite programming language.
You will learn about installing and using NumPy and related concepts. At the end of the book we will explore related scientific computing projects. This book will give you a solid foundation in NumPy arrays and universal functions. Learning NumPy Array will help you be pr ...
NumPy Beginner's Guide, 2nd Edition
NumPy is an extension to, and the fundamental package for scientific computing with Python. In today's world of science and technology, it is all about speed and flexibility. When it comes to scientific computing, NumPy is on the top of the list.
NumPy Beginner's Guide will teach you about NumPy a leading scientific computing library. NumPy replaces a lot of the functionality of Matlab and Mathematica, but in contrast to those products, is free and open source. ...
- Learn advanced Indexing and linear algebra
- Know reshaping automatically
- Dive into Broadcasting and Histograms
- Profile NumPy code and visualize your profiling results
- Speed up your code with Cython
- Use the array interface to expose foreign memory to NumPy
- Use universal functions and interoperability features
- Learn about Matplotlib and Scipy which is often used in conjunction with NumPy ...
SciPy and NumPy
Want to learn SciPy and NymPy quickly? Cut through the complexity of online documentation with this concise and illustrated book, and discover how easily you can get up to speed with these Python libraries. You'll understand why they're powerful enough for many of today's leading scientists and engineers.
Learn how to use NumPy for numerical processing, including array indexing, math operations, and loading and saving data. With SciPy, you'll work with advanced mathematical functions such as optimization, interpolation, integration, clustering, statistics, and other tools that take scientific programming to a whole new level. ...
An action-packed guide for the easy-to-use, high performance, Python based free open source NumPy mathematical library using real-world examples.
The first and only book that truly explores NumPy practically. Perform high performance calculations with clean and efficient NumPy code. Analyze large data sets with statistical functions. Execute complex linear algebra and mathematical computations. ...