The Python Workshop

• Learn how to write clean and concise code with Python 3
• Understand classes and object-oriented programming
• Tackle entry-level data science and create engaging visualizations
• Use Python to create responsive, modern web applications
• Automate essential day-to-day tasks with Python scripts
• Get started with predictive Python machine learning

You already know you want to learn Python, and a smarter way to learn Python 3 is to learn by doing. The Python Workshop focuses on building up your practical skills so that you can work towards building up your machine learning skills as a data scientist, write scripts that help automate your life and save you time, or even create your own games and desktop applications. You'll learn from real examples that lead to real results.Throughout The Python Workshop, you'll take an engaging step-by-step approach to understanding Python. You won't have to sit through any unnecessary theory. If you're short on time you can jump into a single exercise each day or spend an entire weekend learning about Python scripting. It's your choice. Learning on your terms, you'll build up and reinforce key skills in a way that feels rewarding. Every physical print copy of The Python Workshop unlocks access to the interactive edition. With videos detailing all exercises and activities, you'll always have a guided solution. You can also benchmark yourself against assessments, track progress, and receive free content updates. You'll even earn a secure credential that you can share and verify online upon completion. It's a premium learning experience that's included with your printed copy. To redeem, follow the instructions located at the start of your Python book. Fast-paced and direct, The Python Workshop is the ideal companion for Python beginners. You'll build and iterate on your code like a software developer, learning along the way. This process means that you'll find that your new skills stick, embedded as best practice. A solid foundation for the years ahead.

• Ideal for the Python beginner who is getting started for the first time
• A step-by-step Python tutorial with exercises and activities that help build key skills
• Structured to let you progress at your own pace, on your own terms
• Use your physical print copy to redeem free access to the online interactive edition

Table of contents

1 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
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
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
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
Introduction
Classes and Objects
Defining Classes
The __init__ method
Methods
Properties
Inheritance
Summary

6 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
Introduction
Using List Comprehensions
Set and Dictionary Comprehensions
Default Dictionary
Iterators
Itertools
Generators
Regular Expressions
Summary

8 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
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
Introduction
NumPy and Basic Stats
Matrices
The pandas Library
Data
Null Values
Visual Analysis
Summary

11 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