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Learn Python by Building Data Science Applications

Learn Python by Building Data Science Applications

By : Kats, Katz
2.8 (4)
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Learn Python by Building Data Science Applications

Learn Python by Building Data Science Applications

2.8 (4)
By: Kats, 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)
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1
Section 1: Getting Started with Python
11
Section 2: Hands-On with Data
17
Section 3: Moving to Production

Packaging and Testing with Poetry and PyTest

Until now, all our code has lived in either notebooks or Python files. While that is totally fine, with the growth in volume and complexity of our code, it is increasingly becoming a good idea to form one or more go-to sources for the code we use most frequently, as well as sources for the complex code that we don't want to risk adding mistakes to.

In this chapter, we will learn how to build our own packages for use in multiple projects or to be easily shared with others, using the poetry package. A package can work as a deliverable—something you can pass to or share with your client! Building and testing packages is a vital skill that increases your productivity and allows you to save time and reduce stress by enabling you to reuse the same properly tested body of code again and again.

Building packages also likely to...

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