Python Programming

This book is designed to introduce students to programming and software development through the lens of exploring data. You can think of the Python programming language as your tool to solve data problems that are beyond the capability of a spreadsheet.

The user-friendly, object-oriented programming language Python is quickly becoming the most popular introductory programming language for both students and instructors.

This is a free book on programming using the Python language. It serves as a tutorial or guide to the Python language for a beginner audience. If all you know about computers is how to save text files, then this is the book for you. This book is written for the latest Python 3, even though Python 2 is the commonly found version of Python today (read more about it in Python 2 versus 3 section).

These excellent tutorials provide everything you need to know to get started with NumPy.

If you are new to programming with Python and are looking for a solid introduction, this is the book for you. Developed by computer science instructors, books in the "for the absolute beginner" series teach the principles of programming through simple game creation.

This book is aimed at more experienced Python programmers who are looking to deepen their understanding of the language and modern programming idioms. Much of the material focuses on some of the more advanced techniques used by libraries, frameworks, and applications.

Think Python is an introduction to Python programming for students with no programming experience. It starts with the most basic concepts of programming, and is carefully designed to define all terms when they are first used and to develop each new concept in a logical progression. Larger pieces, like recursion and object-oriented programming are divided into a sequence of smaller steps and introduced over the course of several chapters.

This book is designed to introduce students to programming and computational thinking through the lens of exploring data. You can think of Python as your tool to solve problems that are far beyond the capability of a spreadsheet. It is an easy-to-use and easy-to learn programming language that is freely available on Windows, Macintosh, and Linux computers.

Python is a popular general purpose programming language which is well suited to a wide range of problems. Recent developments have extended Python's range of applicability to econometrics, statistics and general numerical analysis. Python – with the right set of add-ons – is comparable to domain-specific languages such as R, MATLAB or Julia.

This book is a Python tutorial for beginners aiming at teaching spatial data processing. It is used as part of the courses taught in Remote Sensing and GIS at Aberystwyth University, UK.

This book is an example-driven, hands-on tutorial that carefully teaches programmers how to accomplish numerous text processing tasks using the Python language. Filled with concrete examples, this book provides efficient and effective solutions to specific text processing problems and practical strategies for dealing with all types of text processing challenges.

Matplotlib provides a large library of customizable plots, along with a comprehensive set of backends. Through practical, hands-on and straightforward examples, the book guides you through Data Visualization and Exploration using Python and Matplotlib.

The focus of the book is specifically on Python programming, libraries, and tools as opposed to data analysis methodology. This is the Python programming you need for data analysis. You'll learn the latest versions of pandas, NumPy, and Jupyter in the process.

Understand data analysis pipelines using machine learning algorithms and techniques with this practical guide, using Python. You'll be equipped with the skills you need to prepare data for analysis and create meaningful data visualizations for forecasting values from data.

Tis textbook is about computer science. It is also about Python. However, there is much more. The study of algorithms and data structures is central to understanding what computer science is all about. Learning computer science is not unlike learning any other type of difficult subject matter.