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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

First Steps in Coding - Variables and Data Types

Having set up all the tools, you're now ready to dive into development. Fire up Jupyter—in this chapter, we will get our hands dirty with code! We'll start with the concept of variables, and learn how to assign and use them in Python. We will discuss best practices on naming them, covering both strict requirements and general conventions. Next, we will cover Python's basic data types and the operators they support, including integers, decimal numbers (floats), strings, and Boolean values. Each data type has a corresponding behavior, typing rules, built-in methods, and works with certain operators.

At the end of this chapter, we will put everything we learned into practice by writing our own vacation budgeting calculator.

The topics covered in this chapter are as follows:

  • Assigning variables
  • Naming the variables...
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