Book Image

The Python Workshop

By : Olivier Pons, Andrew Bird, Dr. Lau Cher Han, Mario Corchero Jiménez, Graham Lee, Corey Wade
Book Image

The Python Workshop

By: Olivier Pons, Andrew Bird, Dr. Lau Cher Han, Mario Corchero Jiménez, Graham Lee, Corey Wade

Overview of this book

Have you always wanted to learn Python, but never quite known how to start? More applications than we realize are being developed using Python because it is easy to learn, read, and write. You can now start learning the language quickly and effectively with the help of this interactive tutorial. The Python Workshop starts by showing you how to correctly apply Python syntax to write simple programs, and how to use appropriate Python structures to store and retrieve data. You'll see how to handle files, deal with errors, and use classes and methods to write concise, reusable, and efficient code. As you advance, you'll understand how to use the standard library, debug code to troubleshoot problems, and write unit tests to validate application behavior. You'll gain insights into using the pandas and NumPy libraries for analyzing data, and the graphical libraries of Matplotlib and Seaborn to create impactful data visualizations. By focusing on entry-level data science, you'll build your practical Python skills in a way that mirrors real-world development. Finally, you'll discover the key steps in building and using simple machine learning algorithms. By the end of this Python book, you'll have the knowledge, skills and confidence to creatively tackle your own ambitious projects with Python.
Table of Contents (13 chapters)

Summary

In this chapter, you have seen some of the tools and skills needed to transition from being a Python programmer to a Python software engineer. You have learned how to collaborate with other programmers using Git and GitHub, how to manage dependencies and virtual environments with conda, and how to deploy Python applications using Docker. You have explored multiprocessing and investigated tools and techniques used for improving the performance of your Python code. These new skills leave you better equipped to handle the messy real world of collaborative teams working on large problems in production environments. These skills are not just academic but are essential tools for any aspiring Python developer to familiarize themselves with.

The next chapter begins the part of the book on using Python for data science. You will learn about popular libraries for working with numerical data, and techniques to import, explore, clean up, and analyze real-world data.

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