Python

Designed as a textbook for a one or two-term introduction to mathematical statistics for students training to become data scientists, Foundations of Statistics for Data Scientists: With R and Python is an in-depth presentation of the topics in statistical science with which any data scientist should be familiar, including probability distributions, descriptive and inferential statistical methods, and linear modelling. The book assumes knowledge of basic calculus, so the presentation can focus on 'why it works' as well as 'how to do it.' Compared to traditional "mathematical statistics" textbooks, however, the book has less emphasis on probability theory and more emphasis on using software to implement statistical methods and to conduct simulations to illustrate key concepts. All statistical analyses in the book use R software, with an appendix showing the same analyses with Python.The book also introduces modern topics that do not normally appear in mathematical statistics texts but ar

This textbook provides a broad introduction to continuous and discrete dynamical systems. With its hands-on approach, the text leads the reader from basic theory to recently published research materia

For readers who may not be statisticians or data analysts, Sarmento and Costa explain how to analyze data using the Python and R languages. They have particularly in mind, students and researchers

This textbook provides an introduction to the free software Python and its use for statistical data analysis. It covers common statistical tests for continuous, discrete and categorical data, as well

Rigging for Games: A Primer for Technical Artists Using Maya and Python is not just another step-by-step manual of loosely related tutorials. Using characters from the video gameTin, it takes you thro

This text helps beginners develop their own Python programs. Experiments with fully completed programs are provided at the beginning of each chapter, allowing instructors to use the text in CS0 course

A no-nonsense introduction to software design using the Python programming language. Written for people with no programming experience, this book starts with the most basic concepts and gradually adds new material. Some of the ideas students find most challenging, like recursion and object-oriented programming, are divided into a sequence of smaller steps and introduced over the course of several chapters. The focus is on the programming process, with special emphasis on debugging. The book includes a wide range of exercises, from short examples to substantial projects, so that students have ample opportunity to practise each new concept. Exercise solutions and code examples are available from thinkpython.com, along with Swampy, a suite of Python programs that is used in some of the exercises.