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

Understanding a function

What is a function anyway? In programming, a function is a named section of code that encapsulates a specific task and can be used relatively independently of surrounding code. Most (but not all) functions are stateless—their outcome depends solely on the function's explicit inputs.

Functions are ubiquitous in Python code. In fact, we have used some functions already; print is one example. Those functions are part of Python's default arsenal of built-in functions. There are 69 built-in functions in total in modern pandas. Before we start writing functions on our own, let's review these built-in functions first.

In the following sections, we will discuss just a handful of functions that we'll use frequently throughout the book; some others we'll discuss later. We have grouped all functions into four groups depending on the...