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 covered a wide spectrum of compound statements. In particular, we covered the if clause, which allows us to build logical forks – parts of code that are executed if a condition is met. We also discussed two types of loops, which allow us to run the same code multiple times, in repetition. Lastly, we covered try/except/finally and with clauses, which gives us options in terms of catching errors on the fly, without halting execution of the script, and guaranteeing that given connections, such as open files, are handled properly.

This chapter concludes our tour of the basics of the language. By no means have we covered it all! However, from now on, we will depart from the sandbox example and start writing code that is actually useful.

In the next chapter, we'll start communicating with external APIs and process data. See you there!

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