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

Learning about web APIs

First, what is an API? Well, an Application Programming Interface (API) is an interface for working with a specific application programmatically—that is, via code. Think of Twitter bots or email clients—all of them use APIs to work with their corresponding applications (Twitter and email servers, respectively).

An API does not have to involve the web—many local applications on your computer have APIs of their own, so we can interact with them through Python or any other language. In our case, however, we need to work with a web API. Those APIs operate via HTTP requests and responses. Many contemporary APIs follow REST guidelines—a set of six design constraints that were put forward by Roy Fielding. You can learn more about REST architecture via REST API Tutorial (https://restfulapi.net/) or the Packt books cited at the end of...