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

What are data structures?

What exactly do we mean by data structures? Generally speaking, they are objects capable of storing and retrieving an arbitrary number of values of any type in a systematic way. In other words, data structures are similar to basic data types: they can be stored via variables, removed, changed, and more.

Built-in data structures provide a standard and highly performant way to work with bulk data. However, there is simply no silver bullet or one-size-fits-all data structure. The benefits and shortcomings of each are built-in and inseparable from the general design. Let's go through the main data structures and discuss both the pros and cons of each one. The following sections will go over the main data structures in Python, starting with the most popular one: lists.

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