Book Image

Python Real-World Projects

By : Steven F. Lott
5 (1)
Book Image

Python Real-World Projects

5 (1)
By: Steven F. Lott

Overview of this book

In today's competitive job market, a project portfolio often outshines a traditional resume. Python Real-World Projects empowers you to get to grips with crucial Python concepts while building complete modules and applications. With two dozen meticulously designed projects to explore, this book will help you showcase your Python mastery and refine your skills. Tailored for beginners with a foundational understanding of class definitions, module creation, and Python's inherent data structures, this book is your gateway to programming excellence. You’ll learn how to harness the potential of the standard library and key external projects like JupyterLab, Pydantic, pytest, and requests. You’ll also gain experience with enterprise-oriented methodologies, including unit and acceptance testing, and an agile development approach. Additionally, you’ll dive into the software development lifecycle, starting with a minimum viable product and seamlessly expanding it to add innovative features. By the end of this book, you’ll be armed with a myriad of practical Python projects and all set to accelerate your career as a Python programmer.
Table of Contents (20 chapters)
19
Index

Chapter 16
Project 5.2: Simple Multivariate Statistics

Are variables related? If so what’s the relationship? An analyst tries to answer these two questions. A negative answer — the null hypothesis — doesn’t require too many supporting details. A positive answer, on the other hand, suggests that a model can be defined to describe the relationship. In this chapter, we’ll look at simple correlation and linear regression as two elements of modeling a relationship between variables.

In this chapter, we’ll expand on some skills of data analysis:

  • Use of the built-in statistics library to compute correlation measures and linear regression coefficients.

  • Use of the matplotlib library to create images. This means creating plot images outside a Jupyter Lab environment.

  • Expanding on the base modeling application to add features.

This chapter’s project will expand on earlier projects. Look back at Chapter 13, Project 4.1: Visual Analysis...