Book Image

Learn Python by Building Data Science Applications

By : Philipp Kats, David Katz
Book Image

Learn Python by Building Data Science Applications

By: Philipp Kats, David Katz

Overview of this book

Python is the most widely used programming language for building data science applications. Complete with step-by-step instructions, this book contains easy-to-follow tutorials to help you learn Python and develop real-world data science projects. The “secret sauce” of the book is its curated list of topics and solutions, put together using a range of real-world projects, covering initial data collection, data analysis, and production. This Python book starts by taking you through the basics of programming, right from variables and data types to classes and functions. You’ll learn how to write idiomatic code and test and debug it, and discover how you can create packages or use the range of built-in ones. You’ll also be introduced to the extensive ecosystem of Python data science packages, including NumPy, Pandas, scikit-learn, Altair, and Datashader. Furthermore, you’ll be able to perform data analysis, train models, and interpret and communicate the results. Finally, you’ll get to grips with structuring and scheduling scripts using Luigi and sharing your machine learning models with the world as a microservice. By the end of the book, you’ll have learned not only how to implement Python in data science projects, but also how to maintain and design them to meet high programming standards.
Table of Contents (26 chapters)
Free Chapter
1
Section 1: Getting Started with Python
11
Section 2: Hands-On with Data
17
Section 3: Moving to Production

Loops and Other Compound Statements

In the previous chapter, we learned how to create and operate on data structures. Now, let's discuss how to operate on them effectively.

We will first cover loops—a special type of compound statement (code that compounds other code, just like functions)—that allows the same code to be run over and over—any number of times, or even indefinitely. After loops, we will discuss if-else statements—logical forks that allow us to split code execution based on test results. Finally, we will cover two less popular, but still very useful, clauses—try, which helps to save the day if something goes wrong (an error is raised) within the code, and with , which helps to close the context safely (for example, close the file correctly).

Hence, this chapter will cover the following topics:

  • Understanding if, else, and elif...