Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Python Real-World Projects
  • Toc
  • feedback
Python Real-World Projects

Python Real-World Projects

By : Steven F. Lott
4.4 (5)
close
Python Real-World Projects

Python Real-World Projects

4.4 (5)
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)
close
19
Index

16.1 Description

In Chapter 15, Project 5.1: Modeling Base Application we created an application to create a summary document with some core statistics. In that application, we looked at univariate statistics to characterize the data distributions. These statistics included measurements of the location, spread, and shape of a distribution. Functions like mean, median, mode, variance, and standard deviation were emphasized as ways to understand location and spread. The characterization of shape via skewness and kurtosis was left as an extra exercise for you.

The base application from the previous chapter needs to be expanded to include the multivariate statistics and diagrams that are essential for clarifying the relationships among variables. There are a vast number of possible functions to describe the relationships among two variables. See https://www.itl.nist.gov/div898/handbook/pmd/section8/pmd8.htm for some insight into the number of choices available.

We’ll limit ourselves...

Unlock full access

Continue reading for free

A Packt free trial gives you instant online access to our library of over 7000 practical eBooks and videos, constantly updated with the latest in tech
bookmark search playlist download font-size

Change the font size

margin-width

Change margin width

day-mode

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Delete Bookmark

Modal Close icon
Are you sure you want to delete it?
Cancel
Yes, Delete