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.

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Table of Contents (13 chapters)
Preface
Preface
About the Course
Free Chapter
1
1. Vital Python – Math, Strings, Conditionals, and Loops
1. Vital Python – Math, Strings, Conditionals, and Loops
Introduction
Vital Python
Numbers: Operations, Types, and Variables
Python as a Calculator
Strings: Concatenation, Methods, and input()
String Interpolation
String Indexing and Slicing
Slicing
Booleans and Conditionals
Loops
Summary
2
2. Python Structures
2. Python Structures
Introduction
The Power of Lists
Matrix Operations
List Methods
Dictionary Keys and Values
Dictionary Methods
Tuples
A Survey of Sets
Choosing Types
Summary
3
3. Executing Python – Programs, Algorithms, and Functions
3. Executing Python – Programs, Algorithms, and Functions
Introduction
Python Scripts and Modules
Python Algorithms
Basic Functions
Iterative Functions
Recursive Functions
Dynamic Programming
Helper Functions
Variable Scope
Lambda Functions
Summary
4
4. Extending Python, Files, Errors, and Graphs
4. Extending Python, Files, Errors, and Graphs
Introduction
Reading Files
Writing Files
Preparing for Debugging (Defensive Code)
Plotting Techniques
The Don'ts of Plotting Graphs
Summary
5
5. Constructing Python – Classes and Methods
5. Constructing Python – Classes and Methods
Introduction
Classes and Objects
Defining Classes
The __init__ method
Methods
Properties
Inheritance
Summary
6
6. The Standard Library
6. The Standard Library
Introduction
The Importance of the Standard Library
Dates and Times
Interacting with the OS
Using the subprocess Module
Logging
Collections
Functools
Summary
7
7. Becoming Pythonic
7. Becoming Pythonic
Introduction
Using List Comprehensions
Set and Dictionary Comprehensions
Default Dictionary
Iterators
Itertools
Generators
Regular Expressions
Summary
8
8. Software Development
8. Software Development
Introduction
Debugging
Automated Testing
Creating a PIP Package
Creating Documentation the Easy Way
Source Management
Summary
9
9. Practical Python – Advanced Topics
9. Practical Python – Advanced Topics
Introduction
Developing Collaboratively
Dependency Management
Deploying Code into Production
Multiprocessing
Parsing Command-Line Arguments in Scripts
Performance and Profiling
Profiling
Summary
10
10. Data Analytics with pandas and NumPy
10. Data Analytics with pandas and NumPy
Introduction
NumPy and Basic Stats
Matrices
The pandas Library
Data
Null Values
Visual Analysis
Summary
11
11. Machine Learning
11. Machine Learning
Introduction
Introduction to Linear Regression
Cross-Validation
Regularization: Ridge and Lasso
K-Nearest Neighbors, Decision Trees, and Random Forests
Classification Models
Boosting Methods
Summary
Appendix
Appendix
1. Vital Python – Math, Strings, Conditionals, and Loops
2. Python Structures
3. Executing Python – Programs, Algorithms, Functions
4. Extending Python, Files, Errors, and Graphs
5. Constructing Python – Classes and Methods
6. The Standard Library
7. Becoming Pythonic
8. Software Development
9. Practical Python – Advanced Topics
10. Data Analytics with pandas and NumPy
11. Machine Learning

Introduction

Welcome to the Python Workshop. This book is for anyone new to the Python programming language. Our objective is to teach you Python so that you can solve real-world problems as a Python developer and data scientist.

This book will combine theory, examples, exercises, questions, and activities for all core concepts; so that you can learn to use Python best practices to solve real-world problems. The exercises and activities have been chosen specifically to help you review the concepts covered and extend your learning. The best way to learn Python is to solve problems on your own.

The material (in this book) is targeted at beginners but will be equally as beneficial to experienced developers who are not yet familiar with Python. We are not teaching computer science per se, but rather Python, the most beautiful and powerful coding language in the world. If you have never studied computer science, you will learn the most important concepts here, and if you have studied computer science, you will discover tools and tricks for Python that you have never seen before.

Python has become the most popular programming language in the world due to its simple syntax, extensive range, and dominance in the field of machine learning. In this book, you will become fluent in Python syntax, and you will take significant steps toward producing Pythonic code. You will gain experience in Python development, data science, and machine learning.

Many introductory Python books provide full introductions to computer science. Learning computer science with Python is an excellent way to start, but it is not the method of this book. Units on software development and data science are rarely covered in such books. They may be touched upon, but here, they represent 40% of our book.

By contrast, many books on software development and data science are not designed for beginners. If they are, the Python fundamentals that they teach are usually summarized in one brief unit. This book devotes considerable space to Python fundamentals and essentials. Beginners are not only welcome; they are guided every step of the way.

In addition to the unique focus on Python fundamentals and essentials, the fact that the content is written by seasoned educators, data scientists, and developers makes this Python book more than just a text or reference.

Python is not the language of tomorrow; Python is the language of today. By learning Python, you will become empowered as a developer, and you will gain a significant edge over the competition. The journey will be fun, compelling, challenging, and ultimately, rewarding.

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