Book Image

Applied Computational Thinking with Python

By : Sofía De Jesús, Dayrene Martinez
Book Image

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 (21 chapters)
Section 1: Introduction to Computational Thinking
Section 2:Applying Python and Computational Thinking
Section 3:Data Processing, Analysis, and Applications Using Computational Thinking and Python
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Revisiting functions

If you recall from Chapter 8, Introduction to Python, we looked at built-in functions, but we also looked at how we can define our own functions. We are now going to talk about arguments in functions and loops, as we delve deeper into how control flow works in Python.

Let's think about problems that involve range. The range takes two arguments: a minimum and a maximum. However, in Python, I should note that you can just give one argument, which then assumes your minimum is 0. For example, if I write range(8), that's the same as range (0, 8). Take a look at what happens if you type range(2) in the Python shell:

Figure 10.3 – Python range interpretation with one argument

In Figure 10.3, you can see that the program interpreted the code as range(0, 2). But let's say you are always changing your range. Think of the range algorithm we wrote earlier. We are now going to rewrite it using a function. This function now has...