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The Python Workshop Second Edition

The Python Workshop Second Edition - Second Edition

By : Wade, Mario Corchero Jiménez , Bird, Dr. Lau Cher Han, Graham Lee
4.6 (19)
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The Python Workshop Second Edition

The Python Workshop Second Edition

4.6 (19)
By: Wade, Mario Corchero Jiménez , Bird, Dr. Lau Cher Han, Graham Lee

Overview of this book

Python is among the most popular programming languages in the world. It’s ideal for beginners because it’s easy to read and write, and for developers, because it’s widely available with a strong support community, extensive documentation, and phenomenal libraries – both built-in and user-contributed. This project-based course has been designed by a team of expert authors to get you up and running with Python. You’ll work though engaging projects that’ll enable you to leverage your newfound Python skills efficiently in technical jobs, personal projects, and job interviews. The book will help you gain an edge in data science, web development, and software development, preparing you to tackle real-world challenges in Python and pursue advanced topics on your own. Throughout the chapters, each component has been explicitly designed to engage and stimulate different parts of the brain so that you can retain and apply what you learn in the practical context with maximum impact. By completing the course from start to finish, you’ll walk away feeling capable of tackling any real-world Python development problem.
Table of Contents (16 chapters)
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13
Chapter 13: The Evolution of Python – Discovering New Python Features

Introduction

In Chapter 9, Practical Python – Advanced Topics, you learned how to use GitHub to collaborate with team members. You also used conda to document and set up the dependencies for Python programs and docker to create reproducible Python environments to run our code.

We will now shift gears to data science. Data science is booming like never before. Data scientists have become among the most sought-after practitioners in the world today. Most leading corporations have data scientists to analyze and explain their data.

Data analytics focuses on the analysis of big data. As each day goes by, there is more data than ever before – far too much for any human to analyze by sight. Leading Python developers such as Wes McKinney and Travis Oliphant addressed this gap by creating specialized Python libraries – in particular, pandas and NumPy – to handle big data.

Taken together, pandas and NumPy are masterful at handling big data. They are built...

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The Python Workshop Second Edition
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