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Applied Computational Thinking with Python

Applied Computational Thinking with Python - Second Edition

By : Sofía De Jesús, Dayrene Martinez
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Applied Computational Thinking with Python

Applied Computational Thinking with Python

By: Sofía De Jesús, Dayrene Martinez

Overview of this book

Computational thinking helps you to develop logical processing and algorithmic thinking while solving real-world problems across a wide range of domains. It's an essential skill that you should possess to keep ahead of the curve in this modern era of information technology. Developers can apply their knowledge of computational thinking to solve problems in multiple areas, including economics, mathematics, and artificial intelligence. This book begins by helping you get to grips with decomposition, pattern recognition, pattern generalization and abstraction, and algorithm design, along with teaching you how to apply these elements practically while designing solutions for challenging problems. You’ll then learn about various techniques involved in problem analysis, logical reasoning, algorithm design, clusters and classification, data analysis, and modeling, and understand how computational thinking elements can be used together with these aspects to design solutions. Toward the end, you will discover how to identify pitfalls in the solution design process and how to choose the right functionalities to create the best possible algorithmic solutions. By the end of this algorithm book, you will have gained the confidence to successfully apply computational thinking techniques to software development.
Table of Contents (25 chapters)
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1
Part 1: An Introduction to Computational Thinking
10
Part 2: Applying Python and Computational Thinking
16
Part 3: Data Processing, Analysis, and Applications Using Computational Thinking and Python

Using other loops and conditionals

Python offers a variety of ways to iterate through information in addition to the for loop. One of the most commonly used loops is a while loop. When using a while loop, we’re checking for a condition constantly. Again, it’s easier to understand this by looking at an example.

Let’s say we are playing a game and ask the user to provide as many animals as they can. We want to be able to do a few things:

  1. Check whether the player has animals to add.
  2. If yes, append each animal to a list.
  3. If no, end the program and provide the final list.
  4. Provide the final list and a count of how many animals the player was able to enter.

Let’s take a look at an algorithm that does the basics for this game:

ch11_whileLoop1.py

myAnimals = []
print('Let\'s see how many animals you can name. Get ready!')
readyPlayer = input('When you are ready to begin, type y. ')
while readyPlayer ==...
CONTINUE READING
83
Tech Concepts
36
Programming languages
73
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Applied Computational Thinking with Python
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