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

Summary

In this chapter, we learned one of the main pillars of code – functions. Functions allow us to write concise and expressive code that can be reused multiple times. Functions serve as building blocks of our programs – be it report generation, interaction with the APIs, or training the model. We discussed how to declare both standard and anonymous functions, how to set arguments, and their default values, and how to use args and kwargs for more flexible interface design. We also learned how to write good quality documentation strings and add type annotations. Finally, we did rewrite our code from the previous chapter, using functions, which made it slightly more expressive and error-prone.

In the last section, we defined recursion – an approach where a function is called from within itself, and which allows us to solve rather complex tasks with simple...