Coffee Break Python Slicing
This book is 100% complete
Completed on 2019-08-18
About the Book
Why do you waste your time PASSIVELY reading Python books?
Puzzle-based learning is an ACTIVE learning technique. With code puzzles, you will learn faster, smarter, and better.
The Coffee Break Python book series teaches you Python in byte-sized code puzzles. You solve a code puzzle a day while you enjoy your morning coffee. It’s that simple.
What do others have to say?
21,000 online Python students have already improved their coding skills with our unique puzzle-based learning technique:
"I very much enjoy your Finxter.com website because it has some real meat to the problems. Thank you so much for doing this project! I love it!"
"Your site is awesome."
"I found Finxter.com an excellent tool to brush up on my Python skills. I totally love the setup of playing against the questions - such a wonderful idea <3 ... and great questions."
Why should you read this book?
Coffee Break Python Slicing is all about growing your Python expertise—one coffee at a time. The focus lies on the important slicing technique to access consecutive data ranges. Understanding slicing thoroughly is crucial for your success as a Python developer.
This book teaches you everything you need to know about slicing in Python.
As a bonus, you will track your individual Python coding skill level throughout the book.
Who should read this book?
You are slightly beyond beginner-level in Python. For example,
- You have already experience with another programming language—it’s time to tackle Python.
- You are a professional engineer and want to brush up your Python skills.
- You are a student and need to get better at Python for academic courses.
- You have read the first book of our Coffee Break Python series.
So how do you spend your Coffee Break? Python!
2 How to Use This Book
2.1 What Is a Code Puzzle?
2.2 Why Puzzle-based Learning?
2.3 How to Measure Your Python Skills with This Book?
3 A Quick Overview of the Python Language 17
3.2 Basic Data Types
3.3 Complex Data Types
3.5 Functions and Tricks
4 Introduction Slicing
4.1 Intermezzo: Indexing Basics
4.3 The Step Size in Slicing
4.4 Overshooting Indices in Slicing
4.5 Summary Basic Python Slicing
4.6 Frequently Asked Questions
5 Code Puzzles Slicing
6 Final Remarks
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