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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 3, Executing Python – Programs, Algorithms, and Functions, you covered the basics of Python programs and learned how to write algorithms, functions, and programs. Now, you will learn how to make your programs more relevant and usable in the IT world.

In this chapter, you are going to look at file operations. File operations are essential for scripting as a Python developer, especially when you need to process and analyze a large number of files, such as in data science. In companies that deal with data science, you often do not have direct access to a database. Rather, they receive files in text format. These include CSV files for column data and TXT files for unstructured data (such as patient logs, news articles, user comments, and so on).

In this chapter, we will cover the following topics:

  • Reading files
  • Writing files
  • Preparing for debugging (defensive code)
  • Plotting techniques
  • The don’ts of plotting graphs
...
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The Python Workshop Second Edition
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