Practice Python Projects

Abstract

1. Introduction

For the web version of the book, visit https://learnbyexample.github.io/practice_python_projects/

See Version_changes.md to keep track of changes made to the book.

The book can also be viewed as a single markdown file in this repo. See my blogpost on generating pdf/epub from markdown using pandoc if you are interested in the ebook creation process.

2. Objective

Book on basic to intermediate level Python projects

This project demonstrates how Python can be applied to a real-world Data Science problem.

4. Technology Stack

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• Python 3.8 or later
• pip / virtualenv for dependencies
• VS Code, PyCharm or Jupyter Notebook
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/learnbyexample/practice_python_projects.git
cd practice_python_projects

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Turn the analysis into an interactive dashboard
• Automate data refresh with a scheduled job
• Add a predictive model on top of the analysis

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. What is the source of the dataset and how was missing data handled?
2. Which exploratory analysis steps revealed the most useful insight?
3. Why were these particular charts chosen to present the data?
4. Which statistical or ML technique supports the conclusions?
5. How could the analysis be automated or refreshed with new data?

9. Source Code & License

This project is developed by learnbyexample and published on GitHub under the MIT License. Please follow the license terms and credit the original author when you use or modify this code.